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Water supply infrastructure planning in groundwater-dependent regions is often challenged by uncertainty in future groundwater resource availability. Many major aquifer systems face long-term water table decline due to unsustainable withdrawals. However, many regions, especially those in the developing world, have a scarcity of groundwater data. This creates large uncertainties in groundwater resource predictions and decisions about whether to develop alternative supply sources. Developing infrastructure too soon can lead to unnecessary and expensive irreversible investments, but waiting too long can threaten water supply reliability. This study develops an adaptive infrastructure planning framework that applies Bayesian learning on groundwater observations to assess opportunities to learn about groundwater availability in the future and adapt infrastructure plans. This approach allows planners in data scarce regions to assess under what conditions a flexible infrastructure planning approach, in which initial plans are made but infrastructure development is deferred, can mitigate the risk of overbuilding infrastructure while maintaining water supply reliability in the face of uncertainty. This framework connects engineering options analysis from infrastructure planning to groundwater resources modeling. We demonstrate a proof-of-concept on a desalination planning case for the city of Riyadh, Saudi Arabia, where poor characterization of a fossil aquifer creates uncertainty in how long current groundwater resources can reliably supply demand. We find that a flexible planning approach reduces the risk of over-building infrastructure compared to a traditional static planning approach by 40% with minimal reliability risk (<1%). This striking result may be explained by the slow-evolving nature of groundwater decline, which provides time for planners to react, in contrast to more sudden risks such as flooding where tradeoffs between cost and reliability risk are heightened. This Bayesian approach shows promise for many civil infrastructure domains by providing a method to quantify learning in environmental modeling and assess the effectiveness of adaptive planning.

1993) Effect of wastewaters on plant growth and soil properties, Arid Soil Research and Rehabilitation, 7:2,[173][174][175][176][177][178][179] To link to this article: http://dx.Abstract Effects of wastewaters on plant growth and soil properties were studied in a pot experiment. Mean biomass ranged from 159 to 210 g per pot for maize and from 165 to 212 g per pot for sorghum in different water salinity treatments. Mean dry matter yield ranged between 28.9 to 38.3 and 34.9 to 50.4 g per pot in different water salinity treatments for maize and sorghum crops, respectively. The crop yield showed significant increase with increase in water salinity. This was presumably due to the nutrients present in wastewaters, especially the nitrogen. Plant yield decreased slightly at water salinity level of 2330 mg L -1 (TDS), indicating that high water salinity can neutralize the beneficial effects of nutrients in wastewaters. Soil salinity and sodicity increased significantly with corresponding increase in water salinity and sodicity (r values of 0.98 (maize) and 0.98 (sorghum) for soil salinity, and 0.96 (maize) and 0.95 (sorghum) for SAR of soils). The interaction between crop and water treatments was significant for soil salinity (an LSD of 0.48 at p = 0.05) and SAR of soil (an LSD of 2.55 at p = 0.05). Overall, the soil salinity and sodicity was significantly more in sorghum than maize. The results showed that wastewaters can successfully be used to grow corn and sorghum as forage crops, provided 15 to 20% excess water is applied to meet leaching requirements to maintain soil salinity within acceptable limits for optimal agricultural production.