Multi-objective optimized allocation of arid saline farmlands and irrigation water resources for sustainable agriculture

Combined stressors (high soil salinity and saline water irrigation) severely reduce plant growth and sugar beet yield. Seed inoculation with plant growth-promoting rhizobacteria (PGPR) and/or foliar spraying with silica nanoparticles (Si-NP) is deemed one of the most promising new strategies that have the potential to inhibit abiotic stress. Herein, sugar beet (Beta vulgaris) plants were treated with two PGPR (Pseudomonas koreensis MG209738 and Bacillus coagulans NCAIM B.01123) and/or Si-NP, during two successive seasons 2019/2020 and 2020/2021 to examine the vital role of PGPR, Si-NP, and their combination in improving growth characteristics, and production in sugar beet plants exposed to two watering treatments (fresh water and saline water) in salt-affected soil. The results revealed that combined stressors (high soil salinity and saline water irrigation) increased ion imbalance (K+/Na+ ratio; from 1.54 ± 0.11 to 1.00 ± 0.15) and declined the relative water content (RWC; from 86.76 ± 4.70 to 74.30 ± 3.20%), relative membrane stability index (RMSI), stomatal conductance (gs), and chlorophyll content, which negatively affected on the crop productivity. Nevertheless, the application of combined PGPR and Si-NP decreased oxidative stress indicators (hydrogen peroxide and lipid peroxidation) and sodium ions while increasing activities of superoxide dismutase (SOD; up to 1.9-folds), catalase (CAT; up to 1.4-folds), and peroxidase (POX; up to 2.5-folds) enzymes, and potassium ions resulting in physiological processes, root yield, and sugar yield compared to non-treated controls under combined stressors (high soil salinity and saline water irrigation). It is worth mentioning that the singular application of PGPR improved root length, diameter, and yield greater than Si-NP alone and it was comparable to the combined treatment (PGPR+Si-NP). It was concluded that the combined application of PGPR and Si-NP has valuable impacts on the growth and yield of sugar beet growing under combined stressors of high soil salinity and saline water irrigation.

برای بررسی اثر سطوح شوری آب آبیاری و زمان شروع آبیاری با آب شور و لب‌شور بر خصوصیات کمی خربزه دیررس، آزمایشی با 7 تیمار و 3 تکرار در قالب بلوک‌های کامل تصادفی با استفاده از روش آبیاری قطره‌ای نواری، در مرکز تحقیقات کشاورزی و منابع طبیعی خراسان رضوی انجام شد. تیمارهای آبیاری عبارت بودند از: 1- آبیاری با آب شیرین (6/0 دسی‌زیمنس بر متر) از ابتدای کاشت تا انتهای فصل برداشت، 2- آبیاری با آب با شوری 3 دسی‌زیمنس برمتر از ابتدا تا انتهای فصل داشت، 3-آبیاری با آب با شوری 6 دسی‌زیمنس بر متر از ابتدا تا انتهای فصل، 4- آبیاری با آب با شوری 6 دسی‌زیمنس بر متر از 20 روز بعد از جوانه‌زنی تا انتها، 5- آبیاری با آب با شوری 3 دسی‌زیمنس بر متر از 20 روز بعد از جوانه‌زنی تا انتها، 6- آبیاری با آب با شوری 6 دسی‌زیمنس بر متر از 40 روز بعد از جوانه‌زنی تا انتها و 7- آبیاری با آب با شوری 3 دسی زیمنس بر متر از 40 روز بعد از جوانه‌زنی تا انتهای فصل داشت. نتایج نشان داد که، شوری آب بر عملکرد کل، عملکرد اقتصادی و کارآیی مصرف آب آبیاری تاثیر معنی‌داری داشت. بالاترین عملکرد کل و عملکرد اقتصادی و کارآیی مصرف آب آبیاری از تیمار شاهد بدست آمد که تفاوت آن‌ها با تیمارهای آب شور و لب‌شور معنی‌دار بود. در ضمن تفاوت بین عملکردهای تیمارهای شور و لب‌شور معنی‌دار نبودند. آبیاری با آب شیرین در اوایل دوره رشد باعث افزایش محصول نشده بلکه، باعث وارد شدن تنش بیشتر به گیاه می‌شود.

Allocation and management of agricultural water resources is an emerging concern due to diminishing water supplies and increasing water demands. To achieve economic, social, and environmental goals in a specific irrigation district, decisions should be made subject to the changing water supply and water demand—the two critical random parameters in agricultural water resources management. This paper presents the foundations of a systematic framework for agricultural water resources management, including determination of distribution functions, joint probability of water supply and water demand, optimal allocation of agricultural water resources, and evaluation of various schemes according to agricultural water resources carrying capacity. The maximum entropy method is used to estimate parameters of probability distributions of water supply and demand, which is the basic for the other parts of the framework. The entropy-weight-based TOPSIS method is applied to evaluate agricultural water resources allocation schemes, because it avoids the subjectivity of weight determination and reflects the dynamic changing trend of agricultural water resources carrying capacity. A case study using an irrigation district in Northeast China is used to demonstrate the feasibility and applicability of the framework. It is found that the framework works effectively to balance multiple objectives and provides alternative schemes, considering the combinatorial variety of water supply and water demand, which are conducive to agricultural water resources planning.

The matching status of agricultural water and land resources is a prerequisite for grain production. The influence of gray water footprint has not been paid attention to in the study of agricultural water and land resources matching based on water footprint. To measure the matching status of agricultural water and land resources more comprehensively, the total water footprint (including blue, green and gray water footprint) and the cultivated land area was taken as the characterization parameters of water and land resources, respectively. The Gini coefficient model, and the agricultural water and land resources matching coefficient model were constructed to calculate the matching degree of agricultural water and land resources in a cold region (Heilongjiang Province) of China. Based on the amount of agricultural water consumption, the equivalent coefficient model was used to evaluate the degree of agricultural water and land resources shortage or to be developed. The result of agricultural water and land resources matching coefficient model showed that the matching degree of agricultural water and land resources in Heilongjiang Province is getting better year by year, which is consistent with the calculations determined from the Gini coefficient. The result of the equivalent coefficient method based on agricultural water consumption was consistent with the result of the Gini coefficient method based on total water footprint, which is verified that it is scientific and reasonable to take the total water footprint as the characterization parameter of water resource. The findings may provide implications for the spatial optimal allocation of regional agricultural water and land resources.

Construction and application of a refined index for measuring the regional matching characteristics between water and land resources

Brackish water used for irrigation can restrict crop growth and lead to environmental problems. The alternate irrigation with saline water at different growth stages is still not well understood. Therefore, field trials were conducted during 2015–2018 in the NCP to investigate whether alternate irrigation is practicable for winter wheat production. The treatments comprised rain-fed cultivation (NI), fresh and saline water irrigation (FS), saline and fresh water irrigation (SF), saline water irrigation (SS) and fresh water irrigation (FF). The results showed that the grain yield was increased by 20% under SF and FS treatments compared to NI, while a minor decrease of 2% in grain yield was observed compared with FF treatment. The increased soil salinity and risk of long-term salt accumulation in the soil due to alternate irrigation during peak dry periods was insignificant due to leaching of salts from crop root zone during monsoon season. Although Na+ concentration in the leaves increased with saline irrigation, resulting in significantly lower K+:Na+ ratio in the leaves, the Na+ and K+ concentrations in the roots and grains were not affected. In conclusion, the alternate irrigation for winter wheat is a most promising option to harvest more yield and save fresh water resources.

Salt stress is abiotic stress that limits plant growth, crop productivityas well as the main factor contributing to land degradation. This study was conducted to evaluate the ameliorative effect of chicken manure and biochar applications used as soil amendments inalleviating the adverse effects of saline water irrigation on plant attributes and macro nutrients uptake by coriander (Coriandrum sativum) plant grown on a sandy textured soil. The ameliorative effect of soil amendments was also evaluated on the properties of the soil and nutrients availability for the plant. For this purpose, a pot experiment was conducted on coriander plant at The Experimental Farm of the Faculty of Agriculture, Mansoura University, Dakahlia Governorate, Egypt. A split plot design with three replications was used during the spring season of 2016. Treatments were the combination of two types of organic amendments (chicken manure and biochar) and three saline irrigation water treatments, .i.e. non-saline water (control) (S0 = 0.45 dS m-1) and saline water (S1= 3.12 dS m-1, 5% and S2 = 6.25 dS m-1, 10%) irrigation. Obtained results showed that soil productivity, as indicated by the vegetative growth and physiological aspects (plant height, leaves fresh and dry weight, no. of leaves/plant and total chlorophyll) for coriander plant were adversely and significantly affected by saline water irrigation. Addition of chicken manure and biochar significant increased the vegetative growth and physiological parameters due to their ameliorative effect. It had been observed a significantly increased in plant N, P and K contents and uptake by plant due to the addition of chicken manure and biochar amendments under saline and non-saline water irrigation compared to unamended one. The contents and uptake of N, P and K in coriander leaves decreased significantly as salinity of irrigation water increased from (S0) to (S2). Soil pH and EC values increased significantly in saline water irrigation treatments (S1 and S2) compared to non-saline water (S0). Soil pH and EC values decreased in soil amended with chicken manure and biochar application under three water types. The reduction in EC values in soil amended with biochar was higher than those in soil amended with chicken manure under all salinity levels. While, the reduction in soil pH values in soil amended with chicken manure was higher than those in soil amended with biochar. Soil available Na+, K+, Ca2+ and Mg2+ concentrations increased with increases in irrigation water salinity, while available P and Zn concentrations were decreased. Soluble Na+ significantly decreased but K+, Ca2+ and Mg2+ increased as a result of amendments application under three water types used. Soil P and Zn availability increased after applying different soil amendments, the concentration of available P in chicken manure amended soil was higher than those in biochar amended soil. While, available Zn concentration in biochar amended soil was higher than unamended one. In conclusion, chicken manure and biochar added to soil as amendments have the potential to mitigate the negative effects of salt stress mainly related to their ability to improve soil physio-chemical properties, promote vegetative growth of coriander plant, increases soil content of organic matter and available nutrient uptake.

It is important to analyze the efficiency of agricultural water and land resources utilization in macro-regions from the perspective of synergistic inputs and "economic-social-ecological" benefits for the sustainability of agricultural production. This paper clarified the connotation of agricultural water and land resources use efficiency by combining the broad concept of water resources and the characteristics of "multiple inputs - multiple outputs" in agricultural production, constructed the Super-SBM(Super slacks based measure) model and Super-Undesirable-SBM(Super undesirable slacks based measure) model using data envelopment analysis to measure the production allocation efficiency. The Super-SBM model and Super-Undesirable-SBM model were used to measure the efficiency of agricultural water and land resources utilization of the concept. Agricultural water and land resources utilization efficiency without considering ecological benefits (WLUE), agricultural water and land resources utilization efficiency with considering ecological benefits (WLUEE), water resource utilization efficiency loss (WUEL) and arable land resource utilization efficiency loss (LUEL) were measured for 51 counties in the study area, taking the Shandong Yellow Diversion Irrigation District as an example. By comparing and analyzing the WLUE and WLUEE measurement results, WUEL and LUEL decomposition results, the characteristics of agricultural water and soil resource utilization and the size difference of the two resource utilization efficiency losses in each county of the study area were revealed, and the counties of the study area were classified into four types: green and efficient production type, ordinary efficient production type, green and inefficient production type and ordinary inefficient production type. This paper proposed targeted improvement measures for agricultural soil and water resource use efficiency in each county and a new perspective for the study of agricultural soil and water resource utilization efficiency. The research results are conducive to promoting the sustainable development of agricultural production in the study area.

Aiming at the problems existing in the current use of agricultural water and land resources in China and in order to realize sustainable use of the two resources, we established an indicator system for comprehensive evaluation of agricultural water and land resources carrying capacity based on the Driving forces-Pressures-States-Impacts-Responses (DPSIR) concept framework. Then we took Sanjiang Plain as study area (including 6 cities and 1 county) and used projection pursuit (PP) model to evaluate regional agricultural water and land resources carrying capacity. The evaluation results indicated that seven indicators, including the arable wasteland rate, water resources utilization rate, urbanization rate, chemical fertilizer application in farmland per unit area, farmland irrigation rate, production GDP per unit water consumption and agricultural land output rate, were the key factors influencing agricultural water and land resources carrying capacity in Sanjiang Plain. Jiamusi, the main agricultural region of Sanjiang Plain, has the lowest carrying capacity of agricultural water and land resources. However, Muling has the highest carrying capacity. The evaluation results could provide scientific guidance for regional agricultural water and land resources sustainable use.

Regional agricultural water resources management with respect to fuzzy return and energy constraint under uncertainty: An integrated optimization approach

Mulching and water quality effects on soil salinity and sodicity dynamics and cotton productivity in Central Asia

Affected by the temporal and spatial changes of natural resources, human activities, and social economic system policies, there are many uncertainties in the development, utilization, and management process of irrigation district agricultural water resources, which will increase the complexity of the use of irrigation district agricultural water resources. Decision makers find it challenging to cope with the complexity of fluctuating water supplies and demands that are critical for water resources’ allocation. In response to these issues, this paper presents an optimization modeling approach for agricultural water allocation at an irrigation district scale, considering the uncertainties of water supply and demand. The minimum cross-entropy method was used to estimate the parameters of hydrologic frequency distribution functions of water supply and demand, which are the basis for agricultural water resources’ optimal allocation and the evaluation of water resources’ carrying capacity in the Hetao Irrigation District. Interval Linear Fractional Programming was used to find water availability, shortage, and use efficiency in different irrigation areas of the Hetao Irrigation District (HID) under different scenarios. The denominator of fractional planning is the environmental goal, and the numerator is the economic goal; so, the objective function of fractional programming is the utility rate required in the post-optimization analysis. Future water availability and shortage scenarios are adopted consistent with the Representative Concentration Pathways’ (RCPs’) framework, and future water use scenarios are developed using the Shared Socioeconomic Pathways’ (SSPs’) framework. Results revealed that under SSP1, the annual water consumption increased from 30 billion m3 to 60 billion m3, almost doubling in Urad. The annual water consumption under SSP2 and SSP3 increased slightly, from 30 billion m3 to about 50 billion m3. The amount of water available for well irrigation in Urad decreased from 300 to 250 billion m3, while the amount of water available for canal irrigation in Urad remained at 270 billion m3 from 2010 s to 2030 s, only dropping to 240 billion m3 in 2040 s. The entropy-weight-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method was applied to evaluate agricultural water resources’ allocation schemes because it can avoid the subjectivity of weight determination and can reflect the dynamic changing trend of irrigation district agricultural water resources’ carrying capacity. The approach is applicable to most regions, such as the Hetao Irrigation District in the Upper Yellow River Basi with limited precipitation, to determine water strategies under the changing environment.

The optimal allocation of agricultural water and land resources is of great significance in ensuring sustainable food production and economic benefits of farmers. However, agriculture, as an important carbon cycle ecosystem, has paid limited attention to carbon sequestration in the optimal allocation of water and land resources. Therefore, this study developed a new water-carbon-economy coupling model (WCECM) for optimal allocation of agricultural water and land resources. In this model, the minimum water scarcity, maximum carbon sequestration and maximum economic benefits are taken as the optimization objectives. In addition, surface water volume and groundwater volume and planting area etc. were defined as constraints, respectively. Then, the model was solved using the Non-dominated Sorting Genetic Algorithm III (NSGA-III) and the Entropy-weighted-TOPSIS evaluation method. The developed model was demonstrated in the largest Farm, Youyi Farm, which is one of commercial grain production base in China to analyze the optimization of water and land resources from 2010 to 2019. We found that the new WCECM, based on the simulation of a complex coupled water-carbon-economy system, can realize the optimal allocation of agricultural water and land resources to protect regional water resources, increase carbon sequestration and adjust the agricultural planting structure. In detail, through the multi-objective optimization model, the planting structure and the allocation ratio of surface water and groundwater irrigation water consumption are more suitable for this study area. After the optimization, the area planted with Rice was significantly reduced, the area planted with Maize was increased, and the area planted with Soybean did not change significantly compared with the first two crops. The planting structure has changed from focusing on paddy cultivation to dryland cultivation, with the ratio of Rice area, Maize area and Soybean area being 3:6:1. The water consumption is constrained within manageable limits, with an average annual irrigation water consumption of 2.01 × 108 m3. The amount of carbon sequestered has increased significantly, with an average annual increase of 7.8 × 108 kg. Meanwhile, the optimized economic benefits increased slightly, with a value of ¥2.35 billion. In short, optimization of water and land resources is beneficial for improving farmers' incomes, increasing carbon sequestration in agriculture, and conserving water resources.

Agricultural water productivity (AWP), which is associated with multiple factors, is an important index for measuring the effectiveness of agricultural water management. The purpose of this study is to promote AWP through optimally allocating limited agricultural water resources with the coordination of related elements. Firstly, the coordination effects of multiple factors related to AWP are quantified as relative optimum membership degrees based on the fuzzy optimum selecting theory. Secondly, based on the relative optimum membership degrees for various crops, a linear fractional programming model is established to maximize AWP in agricultural water resources allocation. Thirdly, the impacts of the allocation schemes on the development of social-economy and ecological environment are discussed using the multi-dimensional regulation theory. The developed integrated system has advantages in increasing agricultural water productivity through the coordination of multiple factors with aspects of economy, society and resources. Moreover, the system is capable of screening schemes considering harmonious development of resources, economy, society and ecology based on optimization results, providing decision makers with more sustainable schemes for irrigation water allocation. The integrated system including the aforementioned three parts is applied to a real-world case study in China to demonstrate its feasibility and applicability. Different water allocation schemes for various crops under different scenarios were obtained. The average value of AWP is 1.85 kg/m3, which is 0.31 kg/m3 higher than the current value of AWP. An optimum scheme with 1.1405 × 108 m3 of water being allocated was also selected due to its highest level of coordination for resources, economy, society and ecology. The developed system can provide an effective method for AWP promotion. The obtained results can help local decision makers adjust water resources allocation schemes.

Water and land resources are related to the security and stability of agricultural production, and the degree of matching in time and space directly affects regional agricultural production capacity and sustainable agricultural development. This paper intends to use the panel data of nine provinces in the Yellow River Basin from 2000 to 2019 and incorporate the static and dynamic spatial Durbin models with spatial effects under the geographical adjacency matrix and the comprehensive weight matrix of economic geography, so as to explore the direct effects and indirect effects, short-term effects and long-term effects of the matching coefficient of agricultural water and land resources on the agricultural economic growth in the Yellow River Basin. The results show the following: (1) The matching situation of agricultural water and land resources in different provinces along the Yellow River Basin are different; some are relatively short of water resources, some are relatively balanced in water and land resources, and some are relatively short of land resources. (2) The static spatial Durbin model shows that the direct effect of the matching coefficient of agricultural water and land resources on the agricultural economic growth of the province is not significant; the indirect effect and the total effect of the spatial spillover is significantly positive. (3) The dynamic spatial Durbin model under the two matrix forms shows that the short-term total effect of the matching coefficient of agricultural water and land resources on agricultural economic growth is significantly positive, while the long-term total effect is significantly negative, and the direction and degree of the short-term and long-term effects are inconsistent. This study provides a comprehensive analysis framework from the perspective of local and neighborhood effect, and short-term and long-term effect, which can provide a reference to reasonably adjust the matching of agricultural water and land resources to promote agricultural sustainable economic growth, especially for developing countries.