Study on the Optimization of Dry Land Irrigation Schedule in the Downstream Songhua River Basin Based on the SWAT Model

The adaptability and irrigation constraints analysis of the WOFOST model for grain production in the Songhua River Basin

BACKGROUND

The Songhua River Basin, a vital grain-producing area in China, faces challenges due to the uneven distribution of water resources and the intensive water demands of agriculture. To enhance agricultural development and effectively manage water scarcity, it is essential to identify the water-saving potential of major staple crops - corn, wheat, and rice. This study enhances the World Food Studies (WOFOST) model by refining the day of year for the developmental vegetative stage (DVS), thereby improving the representation of phenological stages for spring maize, spring wheat, and rice within the model. This refinement offers a detailed analysis of the potential and rainfed yields.

RESULTS

The results from the modified WOFOST model show promising simulation outcomes for the biomass and yield of maize, wheat, and rice, with Nash-Sutcliffe efficiency (NS) and index of agreement (IoA) values all exceeding 0.7. An analysis of photothermal potential yields (Yp) and rainfed yields (Yr) revealed minimal differences in yields for spring maize and rice across various rainfall frequencies. Specifically, the average photothermal utilization rates (LTs) are 93.57% for maize and 85.25% for rice. In contrast, the rainfed yield for wheat is lower than its photothermal yield, with an LT of 43.66%.

CONCLUSIONS

These findings suggest that in the Songhua River Basin, maize and rice offer greater potential for water conservation compared to wheat. It is recommended to judiciously reduce irrigation during the growing seasons of spring maize and rice to help alleviate agricultural water use pressures. © 2024 Society of Chemical Industry.

Evaluation of Irrigation Water Resources Availability and Climate Change Impacts—A Case Study of Mwea Irrigation Scheme, Kenya

Rice is an important cereal crop in Kenya, where it is mainly grown in the Mwea Irrigation Scheme, MIS. The serious challenges of MIS include low water use efficiency and limited available water resources. The objective of this study is to analyze the current and future irrigation water resource availability for the improvement of future water management. A Soil Water Assessment Tool (SWAT), a public domain software supported by the United States Department of Agriculture’s Agricultural Research Service in Bushland, TX, USA, was used to estimate the current and future water resources availability from the MIS’s main irrigation water supply sources (River Thiba and River Nyamindi). CropWat, a computer program developed by the Land and Water Division of the Food and Agriculture Organization (FAO), Rome, Italy, was used to estimate irrigation water requirements from 2013–2016 and into the future (2020–2060 and 2061–2099). Future climatic data for total available flow and irrigation requirement estimations were downloaded from three General Circulation Models (GCMs). The data was bias corrected and down-scaled (with observed data) using a Climate Change Toolkit, a toolkit for climate change analysis developed by the Water Weather and Energy Ecosystem, Zurich, Switzerland. The results indicated that the highest irrigation water deficits were experienced in July and August based on the existing cropping pattern. Under a proposed future pattern, estimates show that MIS will experience water deficits mainly from June to October and from January to February. This study recommends that MIS management should put into strong consideration the simulated future estimates in irrigation water availability for the improvement of water management.

Determining Irrigation Depths for Soybean Using a Simulation Model of Water Flow and Plant Growth and Weather Forecasts

A new scheme to determine irrigation depths using a two-point of predicted cumulative transpiration over irrigation interval is presented. Rather than maximizing water use efficiency, this scheme aims to maximize net income. The volumetric water price is considered to give farmers an incentive to save irrigation water. A field experiment for soybeans was carried out in the Arid Land Research Center, Tottori University, Japan in 2019. The total irrigation amount yield and net income by the proposed scheme were compared to those by a tensiometer-operated automated irrigation. The scheme could save irrigation water by 16% with a yield increment of 20%; resulting in a 22% increase in net income compared to the automated irrigation. The model simulated the volumetric water content in the effective root zone of the plant in fair agreement. These results indicate the effectiveness of the proposed scheme that may replace an automated irrigation system even considering uncertainty in weather forecast to determine irrigation depth and secure investment costs.

Decision-Making of Irrigation Scheme for Soybeans in the Huaibei Plain Based on Grey Entropy Weight and Grey Relation–Projection Pursuit

To provide a scientific reference for formulating an effective soybean irrigation schedule in the Huaibei Plain, potted water deficit experiments with nine alternative irrigation schemes during the 2015 and 2016 seasons were conducted. An irrigation scheme decision-making index system was established from the aspects of crop water consumption, crop growth process and crop water use efficiency. Moreover, a grey entropy weight method and a grey relation–projection pursuit model were proposed to calculate the weight of each decision-making index. Then, nine alternative schemes were sorted according to the comprehensive grey relation degree of each scheme in the two seasons. The results showed that, when using the entropy weight method or projection pursuit model to determine index weight, it was more direct and effective to obtain the corresponding entropy value or projection eigenvalue according to the sequence of the actual study object. The decision-making results from the perspective of actual soybean growth responses at each stage for various irrigation schemes were mostly consistent in 2015 and 2016. Specifically, for an integrated target of lower water consumption and stable biomass yields, the scheme with moderate-deficit irrigation at the soybean branching stage or seedling stage and adequate irrigation at the flowering-podding and seed filling stages is relatively optimal.