Closing the irrigation water productivity gap to alleviate water shortage in an endorheic basin

Closing the irrigation water productivity (IWP) gap is an effective approach to alleviating water deficits and ensuring food security. However, few studies have attempted to quantify the IWP gap and the potential benefits of closing it. This study adopted the Heihe River Basin, the second-largest inland basin in China, as a typical study area. The aims of this study were to: (1) assess the positive achievements and potential risks triggered by the Heihe Ecological Water Diversion Project (EWDP) according to multi-source and multi-scale measured data; (2) analyze potential approaches to improve the IWP and quantify the potential benefits that can be achieved by closing its IWP gap. The results of this study indicated that the EWDP effectively reallocated surface water resources, replenished groundwater in the lower reaches, and facilitated the recovery of oases and economic development in the downstream regions. However, this project has indirectly led to an imbalance in the groundwater resource between the middle and lower reaches, resulting in decline in groundwater levels and degradation of local vegetation in the midstream regions. In addition, the expansion of cultivated land in the midstream and downstream oases has resulted in the deterioration of farmland environment. The water transfer resulted in a deceleration in the growth of IWP from 2.44 % to 1.15 %, and the existing IWP gap was 1.43 kg/m³ between 1984 and 2017. This study predicted a future increase in the IWP to 2.01 kg/m³ with a reduction in the gap to 0.45 kg/m³ while maintaining food production. The potential for conserving water in the Heihe agricultural region can reach 552 million m³ by reducing the planting area by 10 %, improving irrigation water use efficiency by 20 %, maintaining existing agricultural film inputs, and reducing fertilizer application by 10 %. Following the research recommendations can greatly alleviate the agricultural water shortage and over-extraction of groundwater in the middle reaches and ensure meeting ecological water demand in the lower reaches. This study can act as a reference for sustainable management of an endorheic basin.

Supplementary irrigation for managing the impact of terminal dry spells on the productivity of rainfed rice (Oryza sativa L.) in Fogera Plain, Ethiopia

A terminal dry spell is one of the main limiting factors for rice productions. Therefore, this study was conducted to assess the effect of supplemental irrigation for managing the impact of terminal dry spells on the productivity of different rice varieties grown under rainfed conditions in the Fogera Plain. The experiment was designed in a split-plot design with water regimes as main plot factors and rice varieties as a subplot factor with three replications. The water regimes were: dry planted rainfed rice (farmers practice) (FP), transplanted but not irrigated (IWOI), transplanted and irrigated to saturation (SAT), transplanted and ponding to 1 cm water (PD1), and transplanted and ponding to 3 cm water (PD2). The rice varieties were: X-Jigna (V1), Edget (V2), Hiber (V3), Fogera-1 (V4), and Nerica-4 (V5). The combined effect of PD2 with V1 had the highest grain yield (t/ha) (4.35 t/ha) while FP with V3 had the lowest grain yield (2.12 t/ha). The highest (205%) relative grain yield was obtained when V1 was grown under PD2 followed by V4 under PD2 (199%) and V5 under PD2 (192%) compared to FP with V3. Irrigation water productivity (WP_IR) varied between water regimes x varieties from as low as 1.84kg grain mm^-1ha^-1 for V3 in FP to as high as the yield of 3.07kg grain mm^-1ha^-1 for V1 in PD2. The highest and lowest net benefits were recorded for V1 grown under PD2 (65, 550 ETB) and for V3 grown under TWOI (33, 500 ETB ha^-1), respectively. Hence, the combined application of 3 cm ponding depth (PD2) with X-Jigna (V1) and 1cm ponding depth with Fogera-1 (V4) rice varieties could be suggested as effective terminal stress management to increase the yield and profitability of rainfed rice in the Fogera Plain and similar agro-ecologies.

A bi-level multiobjective stochastic approach for supporting environment-friendly agricultural planting strategy formulation

In this study, integration of analytic hierarchy process method and entropy method (AHP-EW) for quantifying the knowledge and experience accumulated by regional managers as well as the socioeconomic situation, the partial least squares regression (PLS) for reflecting the relationship between irrigation water use efficiency and agronomic inputs, and the ecosystem service value for measuring environmental impacts of changing crop planting area were considered in one framework simultaneously. With help of these efforts, a bi-level multiobjective stochastic approach to improve irrigation water use efficiency and decrease the pollution production of agronomic measures in the process of agricultural production. The proposed framework integrate bi-level multiobjective programming and stochastic expectation programming to not only make tradeoffs among multiple concerns from two-level decision makers, but also deal with the randomness of runoff. Then, the proposed approach was applied to a real-world case in the middle reaches of the Heihe River basin, northwest China. Results show that the developed approach can improve irrigation water use efficiency, reduce CO₂ emission, expand ecosystem service values, and provide more profitable and environment-friendly agricultural planting strategies to decision makers, which can further contribute to the sustainable development of agriculture. Furthermore, by comparing the bi-level multiobjective stochastic programming (BMSP) model with the other six models originated from developed model, it can be found that 1) the single objective model can obtain the best value of that objective, but cannot readily consider other important aspects; 2) the multiobjective models can make tradeoffs among multiple objectives; 3) the BMSP model can reflect the leader-follower relationship in the optimization process. The approach is applicable for arid and semiarid regions that face similar problems to determine agricultural planting strategies.