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1 Yang, R.; Xu, H. 2023. Does agricultural water-saving policy improve food security? Evidence from the Yellow River Basin in China. Water Policy, 25(3):253-268. [doi: https://doi.org/10.2166/wp.2023.217]

Food security ; Water conservation ; Policies ; Agricultural production ; Agricultural water use ; Political aspects ; Water resources ; Water productivity ; Cultivated land / China / Yellow River Basin

(Location: IWMI HQ Call no: e-copy only Record No: H051803)

https://iwaponline.com/wp/article-pdf/25/3/253/1197187/025030253.pdf
https://vlibrary.iwmi.org/pdf/H051803.pdf

(0.55 MB) (564 KB)

For our empirical research, the 2012 implementation of China's National Agricultural Water-Saving Outline serves as a quasi-experiment. In addition, one of the main regions in China for grain production is the Yellow River Basin. Based on this, we utilize a Difference-in-Difference (DID) empirical technique to assess the impact of the agricultural water-saving policy on food security using data from prefectures in China's Yellow River Basin from 2000 to 2020. According to the estimated results, grain production has greatly increased as a result of the agricultural water-saving policy. This conclusion still holds when other water-related policies are considered. The agricultural water-saving policy may enhance other input factors in grain production by assuring water demand, which is one possible mechanism of the influence. The empirical results show that the policy indeed increases the water productivity in agricultural production, which will ensure the effective water utilization in agricultural production, and the grain sown area, which is the most important production factor in agriculture. In heterogeneity analysis, the impact of the policy on food security is the largest in the lower reach, followed by the middle reach and the smallest in the upper reach in the Yellow River Basin.

2 Xu, H.; Yang, R.; Song, J. 2023. Water rights reform and water-saving irrigation: evidence from China. Water Science and Technology, 88(11):2779–2792. [doi: https://doi.org/10.2166/wst.2023.385]

Water rights ; Reforms ; Water conservation ; Drip irrigation ; Trickle irrigation ; Agricultural production ; Agricultural water use ; Water productivity ; Water extraction ; Grain crops ; Cash crops ; Water scarcity ; Water resources ; Land area ; Cultivated land ; Precipitation / China

(Location: IWMI HQ Call no: e-copy only Record No: H052441)

https://iwaponline.com/wst/article-pdf/88/11/2779/1340235/wst088112779.pdf
https://vlibrary.iwmi.org/pdf/H052441.pdf

(0.60 MB) (612 KB)

As a market-based water resource management, the water rights reform (WRR) will allocate water rights to water users and allow water users to trade water rights, which can realize the reallocation across water users. In this context, the adoption of water-saving irrigation (WSI) is an important technical form to adapt to the reform. Based on this, this paper studies the impacts of the WRR on WSI using the difference-in-differences (DID) strategy. The results show that the WRR could increase the land area for WSI by an average of 13.63%. The WRR could promote the expansion of high-efficiency irrigation mainly because the WRR could promote the expansion of spray and drip irrigation areas, and micro-irrigation land areas, which are high-efficiency water-saving irrigation technologies. In addition, the WRR also could improve agricultural production by increasing agricultural water productivity and planting area (including the sown area of grain crops and cash crops), but the WRR does not reduce agricultural water extraction. Therefore, the WRR could increase agricultural production without increasing agricultural water extraction.

3 Yang, R.; Feng, J.; Tang, J.; Sun, Y. 2024. Risk assessment and classification prediction for water environment treatment PPP projects. Water Science and Technology, 89(5):1264-1281. [doi: https://doi.org/10.2166/wst.2024.052]

Water treatment ; Public-private partnerships ; Risk assessment ; Risk management ; Water management ; Models ; Machine learning ; Social capital

(Location: IWMI HQ Call no: e-copy only Record No: H052727)

https://iwaponline.com/wst/article-pdf/89/5/1264/1381518/wst089051264.pdf
https://vlibrary.iwmi.org/pdf/H052727.pdf

(0.91 MB) (928 KB)

Water treatment public–private partnership (PPP) projects are pivotal for sustainable water management but are often challenged by complex risk factors. Efficient risk management in these projects is crucial, yet traditional methodologies often fall short of addressing the dynamic and intricate nature of these risks. Addressing this gap, this comprehensive study introduces an advanced risk classification prediction model tailored for water treatment PPP projects, aimed at enhancing risk management capabilities. The proposed model encompasses an intricate evaluation of crucial risk areas: the natural and ecological environments, socio-economic factors, and engineering entities. It delves into the complex relationships between these risk elements and the overall risk profile of projects. Grounded in a sophisticated ensemble learning framework employing stacking, our model is further refined through a weighted voting mechanism, significantly elevating its predictive accuracy. Rigorous validation using data from the Jiujiang City water environment system project Phase I confirms the model's superiority over standard machine learning models. The development of this model marks a significant stride in risk classification for water treatment PPP projects, offering a powerful tool for enhancing risk management practices. Beyond accurately predicting project risks, this model also aids in developing effective government risk management strategies.