This study conducted an in-depth systematic review of literature to explore the context of water, sanitation and hygiene (WaSH) sustainability and resilience in refugee communities. Our results indicate growing concerns, given the two-decade waiting period for refugees to achieve repatriation/integration into host communities, and the bulk of their accommodation is largely in the Global South. This makes the sustainability of WaSH increasingly complex and depends on understanding the roles and interdependences among the factors in each specific refugee camp, and recognizes that it is not 'one-size-fits-all' solutions and the sustainability of one camp might not be suitable for other camps.
In order to develop a better model for quantifying aquatic community using environmental factors that are easy to get, we construct quantitative aquatic community models that utilize the different relationships between water environmental impact factors and aquatic biodiversity as follows: a multi-factor linear-based (MLE) model and a black box-based 'Genetic algorithm-BP artificial neural networks' (GA-BP) model. A comparison of the model efficiency and their outputs is conducted by applying the models to real-life cases, referring to the 49 groups of seasonal data observed over seven field sampling campaigns in Shaying River, China, and then performing model to reproduce the seasonal and inter-annual variation of the water ecological characteristics in the Huaidian (HD) site over 10 years. The results show that (1) the MLE and GA-BP models constructed in this paper are effective in quantifying aquatic communities in dam-controlled rivers; and (2) the performance of GA-BP models based on black-box relationships in predicting the aquatic community is better, more stable, and reliable; (3) reproducing the seasonal and inter-annual aquatic biodiversity in the HD site of Shaying River shows that the seasonal variation of species diversity for phytoplankton, zooplankton, and zoobenthos are inconsistent, and the inter-annual levels of diversity are low due to the negative impact of dam control. Our models can be used as a tool for aquatic community prediction and can become a contribution to showing how quantitative models in other dam-controlled rivers to assisting in dam management strategies.
Mangroves are among the most carbon-dense ecosystems worldwide. Most of the carbon in mangroves is found belowground, and root production might be an important control of carbon accumulation, but has been rarely quantified and understood at the global scale. Here, we determined the global mangrove root production rate and its controls using a systematic review and a recently formalised, spatially explicit mangrove typology framework based on geomorphological settings. We found that global mangrove root production averaged ~770 ± 202 g of dry biomass m-2 year-1 globally, which is much higher than previously reported and close to the root production of the most productive tropical forests. Geomorphological settings exerted marked control over root production together with air temperature and precipitation (r2 ≈ 30%, p < .001). Our review shows that individual global changes (e.g. warming, eutrophication, drought) have antagonist effects on root production, but they have rarely been studied in combination. Based on this newly established root production rate, root-derived carbon might account for most of the total carbon buried in mangroves, and 19 Tg C lost in mangroves each year (e.g. as CO2 ). Inclusion of root production measurements in understudied geomorphological settings (i.e. deltas), regions (Indonesia, South America and Africa) and soil depth (>40 cm), as well as the creation of a mangrove root trait database will push forward our understanding of the global mangrove carbon cycle for now and the future. Overall, this review presents a comprehensive analysis of root production in mangroves, and highlights the central role of root production in the global mangrove carbon budget.
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Abstract. This paper investigates the patterns and controls of aquifer–river exchange in a fast-flowing lowland river by the conjunctive use of streambed temperature anomalies identified with Fibre-optic Distributed Temperature Sensing (FO-DTS) and observations of vertical hydraulic gradients (VHG). FO-DTS temperature traces along this lowland river reach reveal discrete patterns with "cold spots" indicating groundwater up-welling. In contrast to previous studies using FO-DTS for investigation of groundwater–surface water exchange, the fibre-optic cable in this study was buried in the streambed sediments, ensuring clear signals despite fast flow and high discharges. During the observed summer baseflow period, streambed temperatures in groundwater up-welling locations were found to be up to 1.5 °C lower than ambient streambed temperatures. Due to the high river flows, the cold spots were sharp and distinctly localized without measurable impact on down-stream surface water temperature. VHG patterns along the stream reach were highly variable in space, revealing strong differences even at small scales. VHG patterns alone are indicators of both, structural heterogeneity of the stream bed as well as of the spatial heterogeneity of the groundwater–surface water exchange fluxes and are thus not conclusive in their interpretation. However, in combination with the high spatial resolution FO-DTS data we were able to separate these two influences and clearly identify locations of enhanced exchange, while also obtaining information on the complex small-scale streambed transmissivity patterns responsible for the very discrete exchange patterns. The validation of the combined VHG and FO-DTS approach provides an effective strategy for analysing drivers and controls of groundwater–surface water exchange, with implications for the quantification of biogeochemical cycling and contaminant transport at aquifer–river interfaces.
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