Irrigation water resources management under uncertainty: An interval nonlinear double-sided fuzzy chance-constrained programming approach

A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

Multi-scale modeling for irrigation water and cropland resources allocation considering uncertainties in water supply and demand

A simulation-based multi-objective two-level optimization decision-making approach for supporting balanced irrigation water management

<p>Water shortage and soil salinization are main limiting factors in agricultural production in arid and semi-arid regions worldwide. Located in western Inner Mongolia of China, the Hetao Irrigation District (HID) is the largest gravity-fed irrigation district in Asia and one of the top three largest irrigation districts in China. Irrigation water overuse and high level of soil salinity are the main challenges that curb agricultural productivity, adversely affect farmers’ revenues, and threaten long-term sustainability of irrigated farming in the HID. Nevertheless, irrigation water allocation, salt leaching and accumulation, crop productivity and farming decisions are intrinsically connected and thus necessitate taking a holistic approach to investigate into the interactions among all those factors and devising appropriate technological, management and policy interventions. Towards this goal, an integrated hydro-agro--economic optimization model was developed to optimize water allocation among sub-irrigation districts, across stable and cash crops, and in the four irrigation events of a year that are unique for the HID. The model optimizes net revenue of the HID considering water and salt balance, the response of crops to salinity and water stress, land availability, and existing irrigation management practices that have been proved effective. The Positive Mathematical Programming (PMP) approach is used to calibrate the model such that it can reproduce base year observations of crop acreage, water uses and production costs and benefits, making the model suitable for evaluating alternative management and policy scenarios. Sensitivity analysis were conducted for initial groundwater table, initial soil salinity level and leaching coefficient, and the results were moderately sensitive to initial soil salinity and marginally sensitive to groundwater table and leaching coefficient values. Scenario analyses were conducted to analyze the effects of irrigation water supply, winter irrigation (non-growing period) water application, irrigation efficiency and crop commodity market prices. We found that water supply reduction increases land fallow and reduces net revenue. Winter irrigation can store soil moisture to increase summer crop planting areas and increase salt-leaching to lower crop salinity stress. However, irrigation water use efficiency improvement can cause unintended negative consequences, such as exacerbated soil salinization. Higher crop commodity market price increases planting areas and water allocation of the crop but reduce areas and water uses of other crops, leading to a “crowding-out” effects. These results and modeling exercises provide a holistic perspective and useful insights for future water, land and salinity management, irrigation infrastructure investment, and market risk management in the HID.</p>

Handheld optical sensor was used to measure canopy reflectance at red region (656 nm) and near-infrared region (774 nm) to generate NDVI data for monitoring rice productivity under soil amendment with combinations of fertilizers at two levels of water regime in smallholder Irrigation Scheme, in Lower Moshi, North Tanzania. The study was carried out in an experimental design which consisted of two irrigation water levels (flooding and system of rice intensification) with multi-nutrients (NPK) and single nutrient (urea) application replicated three times in a randomized complete block design. Flood irrigation water was applied at 7 cm height throughout the growing season, while SRI treatment irrigation water was applied at 4 cm height under alternate wetting and drying conditions. The annual rates of fertilizers applied was 120 kg N/ha, 20 kg P/ha, and 25 kg K/ha. The variety SARO-5 was used in this experiment. Simple correlation coefficient (r) was used to measure the degree of association between field crop performance parameters (plant height, number of tillers, biomass, yield) and NDVI across growth stages and three positions of the sensor above the canopy in the tested fertilizer combinations and water regimes. Results show that at any given fertiliser combinations and water levels, there was no significant correlation between plant height and NDVI except for the plant height at a vegetative stage for 0.6 m above the crop canopy and booting stage at 0.3 m and 0.6 m above the canopy, respectively (P < 0.05). A good correlation was also observed between NDVI at booting and full booting stage regardless of the position of the sensor above the canopy and the number of tillers at full booting growth stage (P < 0.05). A significant relationship was observed between rice grain yield and NDVI at the vegetative, booting, and full booting stage. The simple linear regression models explained only slightly < 30% of the yield predictions by NDVI at the early stage of the crop growth, decreasing gradually to 5% at the full booting growth stage. Results demonstrate a positive linear relationship between rice grain yield and NDVI for the tested soil fertiliser amendments and irrigation water regimes. Thus, we conclude that handheld NDVI-based sensor can be used in smallholder rice yield predictions for optimising soil fertiliser use and irrigation water management. This allows future multi-functional land management within the soil–water-food nexus.

A distributed interval nonlinear multiobjective programming approach for optimal irrigation water management in an arid area

To obtain the optimal trade‐off between economy and reliability, this study presents a fuzzy chance constrained programming (CCP) approach to the day‐ahead scheduling of virtual power plant (VPP). In this model, uncertain factors in VPP are characterised by fuzzy parameters, and reserve requirements are formulated as fuzzy chance constraints. Considering that economy and risk of VPP are sensitive to different confidence levels (CLs), it is important to select a proper CL for the operator. Different from a pre‐given CL in most literatures, this study proposes a method to determine the optimal CL, hoping to provide references for the operator in optimisations involving CCP. A synthetic satisfaction function is introduced, which depicts the satisfaction degree of VPP under different probabilities. Meanwhile, the satisfaction function reflects VPP's distinct attitudes toward risk and profit. A matrix real‐coded genetic algorithm combined with Monte Carlo simulation is used to solve this model. To reduce computation burden, the fuzzy chance constraint is converted into its crisp equivalent by utilising credibility theory. Numerical tests are performed in a VPP system, and the best CL is determined through comparing VPP's satisfaction degree under different cases, which prove the validity of the proposed model.

Untangling the effects of shallow groundwater and deficit irrigation on irrigation water productivity in arid region: New conceptual model

Abstract&#x0D; Analysis is a way to check the availability and irrigation water requirements in an agricultural land. For the purposes of irrigation, enough water is needed to increase agricultural productivity. Performance management of irrigation water at farm level is very varied with irrigation water allocation is less efficient. It is thus this is one major cause actual yields are still low. Then need to arrange for water use and preparation of schedules and appropriate cropping pattern under various conditions. So that would be more effective in using water, expected in the future no water shortage, which in turn will increase productivity pertanian.Yang ultimately to meet national food needs. The research shows that it turns out the availability of water in the reservoir Cipancuh insufficient irrigation water requirements.&#x0D; &#x0D; Keywords : rainfall, dependable flow, cropping patterns and crop species.

One of the alternative methods for managing irrigation water is deficit irrigation, particularly alternate furrow irrigation (AFI). This deficit in irrigation is affected by uncontrolled rainfall. In line with this, rainfall uncertainty causes a variation between the measured actual crop evapotranspiration and the theoretical crop evapotranspiration. Let us imagine that rain falls during the deficit irrigation research, and the soil moisture under the deficit experiment is then raised to the soil field capacity. It is incorrect to report the result as a deficit. Thus, there is a research gap on the effect of rainfall uncertainty on the quantity of theoretical and actual crop evapotranspiration under deficit irrigation. This study was carried out at the Arba Minch University demonstration site on onion crops. Using CROPWAT 8.0 software, the reference evapotranspiration (ETo) was calculated using the Penman-Monteith formula. The crop coefficient and ETo were used to calculate the theoretical crop evapotranspiration. In contrast, actual crop evapotranspiration was calculated using soil moisture measurements before and after each irrigation event after applying theoretical crop evapotranspiration. As a result, there is a significant difference between the calculated theoretical crop evapotranspiration and actual crop evapotranspiration from a deficit study. Thus, the calculated seasonal theoretical crop evapotranspiration was 201.72 mm. On the other hand, the actual crop evapotranspiration was 275.82 mm. This revealed that the actual crop evapotranspiration was greater than the calculated theoretical crop evapotranspiration by 36.7%. Uncontrolled rainfall was identified as the output’s cause. This has an evident effect on the deficit in experimental research. Hence, conducting the deficit experiment in a greenhouse is more reasonable. In addition, it is possible to assess actual crop evapotranspiration based on daily soil moisture measurements and report the deficit level based on the measured amount.

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

A systems approach to drainage reduction in the San Joaquin Valley

In arid and semiarid areas in the world, including the Mediterranean region, groundwater has been widely and intensively used for irrigation over the last few decades. Practical as well as economic reasons make its use much more preferable, as compared to surface water, especially to individual farmers. Yet, this rapid and largely uncontrolled expansion in groundwater exploitation, which stimulated the socioeconomic development of numerous rural communities, has produced many negative impacts on aquifer degradation and environmental deterioration. The most common remedy to such problems is the application of specific groundwater management policies that can simultaneously meet socioeconomic and environmental protection goals. In this sense, the paper introduces a methodology for an optimal management of irrigation water, by specifically exploring the socioeconomic and environmental impacts of spatially allocated water conservation measures at the watershed level. The analysis is conducted by developing a multi-criteria decision-making framework, consisting of three distinct models: a hydrogeological, an optimization, and a multi-criteria one, which appraises the results of the other two. The proposed methodology is presented through a case study at a rural Greek watershed, in which groundwater is the sole water source for an intensively practiced agriculture. A system of water use quotas is the resource conservation policy instrument that is examined under a decision-making approach. Results show that some specifically designed and spatially non-uniform quota allocation schemes can meet in an optimum way the relevant criteria.

Organic carbon and irrigation water scarcity are two major limiting factors in corn (Zea mays L.) production of Fars province which is located in the south of Iran. Soil tillage systems can affect the nitrogen and water utilization. In 2015-2017, by using the strip-split plot design and two line-source sprinkler irrigation systems, effects of 0, 90, 180, and 270 kg.ha-1 of pure nitrogen and 6400, 7500, 8550, and 9600 m3.ha-1 of irrigation water in conventional, and no-tillage systems were investigated. Results showed that conventional tillage system had high WUE and foliage yield than no-tillage systems. Based on the obtained results, in the terms of dry foliage yield, combined application of 8550 m3.ha-1 irrigation water and 90 kg N.ha-1 (I2N90 treatment) are introduced as the superior treatments in both of two tillage systems. While, in terms of WUE, combined application of 8550 m3.ha-1 irrigation water and 90 kg N.ha-1 (I2N90 treatment) in conventional tillage and combined application of 7500 m3.ha-1 irrigation water and 135 kg N.ha-1 (I3N135 treatment) in no-tillage systems are introduced as the superior treatments.

Erratum for “Improved Ant Colony Optimization for Optimal Crop and Irrigation Water Allocation by Incorporating Domain Knowledge” by D. C. H. Nguyen, G. C. Dandy, H. R. Maier, and J. C. Ascough II