B6. Suitability of Using Groundwater Temperature and Geology to Predict Arsenic Contamination in Drinking Water – A Case Study in Central Mexico

Arsenic in drinking water poses a risk to people’s health and can cause skin disorders, irritation of the respiratory and digestive systems and increased risk of cancer. In parts of Irapuato, central Mexico, arsenic levels in groundwater used for drinking water exceed Mexican and World Health Organization drinking level norms, but a cheap and simple method to identify areas at risk of exceeding these norms is lacking. Since previous research suggests a relationship between water temperature and arsenic concentration, and geology may also play a role in elevated levels of arsenic, water managers can possibly use local knowledge on well temperatures with available geological data to identify high-risk areas. To evaluate the suitability of such an approach, data was collected for 111 wells, using well samples collected in the field and government data collected by JAPAMI. Results show that water in 24% of the sampled wells exceeded the Mexican norm of 0.025 mg/l arsenic, while a disturbing 51% exceeded the stricter WHO norm of 0.010 mg/l. There was a fairly good (R2=0.54) positive linear correlation between temperature and arsenic concentration. On average, groundwater >27.4°C exceeded the Mexican arsenic norm, and >25.9°C exceeded the WHO norm, with false negative rates of 7 and 20%, respectively (i.e. cooler water exceeding arsenic norms). Surface geology in Irapuato is dominated by alluvial sediments, volcanic rock, limestone, sandstone and conglomerate. Results show that surface geology has a significant effect on arsenic concentrations, with limestone, and to a lesser degree sandstone and conglomerate, having significantly higher arsenic levels than alluvial sediment and volcanic rock areas. However, the sampled wells were predominately located in alluvial sediment areas, with only 2% of measurements in limestone and 9% in sandstone and conglomerate areas. This research shows that in Irapuato, groundwater temperature can be used to evaluate which areas are likely to exceed arsenic drinking water norms, though additional factors could lower the false negative rate. Wells in consolidated sedimentary rock, particularly limestone, were particularly vulnerable for arsenic contamination. Water managers can use this information to target high-risk areas and for the development of water management and treatment plans

Micro-Catchments, Macro Effects: Natural Water Retention Measures in the Kylldal Catchment, Germany

Floods are among the most devastating and financially burdensome natural disasters in Europe. The combined impact of climate change and land use change is expected to exacerbate and intensify the destructive consequences of river floods. In this study, we analysed the effects of wetland restoration on peak and base flows and on water quality in the Kylldal catchment of the Kyll River in the German Middle Mountains using the Soil and Water Assessment Tool+ (SWAT+). Monthly median daily discharge increases varied between 3% and 33% in the studied (micro)catchments. The higher median flow rates show that discharge peaks were attenuated and distributed over a longer period, making both extreme peak flows and low flows less common. Peak flows tended to decrease, with the largest effects between late fall and early spring when peak flow values decreased by up to 18%. The annual maximum peak flows in each of the three micro-catchments decreased by 12–24% on average. The occurrence of daily average flow rates larger than 1 m3 s−1 was up to 45% lower after wetland restoration. Low flows increased by up to 21% and 13% in the summer and fall, respectively, which suggests that drought risk also decreases after wetland restoration. Average nitrogen exports decreased by 38–50% in the project areas and by 20% at the catchment level. Average phosphorus exports decreased by 52–67% in the project areas and by 25% at the catchment level. The study highlights the potential of wetland restoration for improving hydrological services, mitigating flood risks, and enhancing water quality. Restoring and maintaining freshwater ecosystems and their natural sponge functions is crucial for effectively managing water resources and addressing the challenges posed by climate change and land use changes

Joint assimilation of soil moisture retrieved from multiple passive microwave frequencies increases robustness of soil moisture state estimation

Soil moisture affects the partitioning of water and energy and is recognized as an essential climate variable. Soil moisture estimates derived from passive microwave remote sensing can improve model estimates through data assimilation, but the relative effectiveness of microwave retrievals in different frequencies is unclear. Land Parameter Retrieval Model (LPRM) satellite soil moisture derived from L-, C-, and X-band frequency remote sensing were assimilated in the Australian Water Resources Assessment landscape hydrology model (AWRA-L) using an ensemble Kalman filter approach. Two sets of experiments were performed. First, each retrieval was assimilated individually for comparison. Second, each possible combination of two retrievals was assimilated jointly. Results were evaluated against field-measured top-layer and root-zone soil moisture at 24 sites across Australia. Assimilation generally improved the coefficient of correlation (r) between modeled and field-measured soil moisture. L-and X-band retrievals were more informative than C-band retrievals, improving r by an average of 0.11 and 0.08 compared to 0.04, respectively. Although L-band retrievals were more informative for top-layer soil moisture in most cases, there were exceptions, and L-and X-band were equally informative for root-zone soil moisture. The consistency between L-and X-band retrievals suggests that they can substitute for each other, for example when transitioning between sensors and missions. Furthermore, joint assimilation of retrievals resulted in a model performance that was similar to or better than assimilating either retrieval individually. Comparison of model estimates obtained with global precipitation data and with higher-quality, higher-resolution regional data, respectively, demonstrated that precipitation data quality does determine the overall benefit that can be expected from assimilation. Further work is needed to assess the potentially complementary spatial information that can be derived from retrievals from different frequencies

Can pore-clogging by ash explain post-fire runoff?

Ash plays an important role in controlling runoff and erosion processes after wildfire and has frequently been hypothesised to clog soil pores and reduce infiltration. Yet evidence for clogging is incomplete, as research has focussed on identifying the presence of ash in soil; the actual flow processes remain unknown. We conducted laboratory infiltration experiments coupled with microscope observations in pure sands, saturated hydraulic conductivity analysis, and interaction energy calculations, to test whether ash can clog pores (i.e. block pores such that infiltration is hampered and ponding occurs). Although results confirmed previous observations of ash washing into pores, clogging was not observed in the pure sands tested, nor were conditions found for which this does occur. Clogging by means of strong attachment of ash to sand was deemed unlikely given the negative surface charge of the two materials. Ponding due to washing in of ash was also considered improbable given the high saturated conductivity of pure ash and ash-sand mixtures. This first mechanistic step towards analysing ash transport and attachment processes in field soils therefore suggests that pore clogging by ash is unlikely to occur in sands. Discussion is provided on other mechanisms by which ash can affect post-fire hydrology. Journal compilatio

Joint assimilation of soil moisture retrieved from multiple passive microwave frequencies increases robustness of soil moisture state estimation

Soil moisture affects the partitioning of water and energy and is recognized as an essential climate variable. Soil moisture estimates derived from passive microwave remote sensing can improve model estimates through data assimilation, but the relative effectiveness of microwave retrievals in different frequencies is unclear. Land Parameter Retrieval Model (LPRM) satellite soil moisture derived from L-, C-, and X-band frequency remote sensing were assimilated in the Australian Water Resources Assessment landscape hydrology model (AWRA-L) using an ensemble Kalman filter approach. Two sets of experiments were performed. First, each retrieval was assimilated individually for comparison. Second, each possible combination of two retrievals was assimilated jointly. Results were evaluated against field-measured top-layer and root-zone soil moisture at 24 sites across Australia. Assimilation generally improved the coefficient of correlation (r) between modeled and field-measured soil moisture. L- and X-band retrievals were more informative than C-band retrievals, improving r by an average of 0.11 and 0.08 compared to 0.04, respectively. Although L-band retrievals were more informative for top-layer soil moisture in most cases, there were exceptions, and L- and X-band were equally informative for root-zone soil moisture. The consistency between L- and X-band retrievals suggests that they can substitute for each other, for example when transitioning between sensors and missions. Furthermore, joint assimilation of retrievals resulted in a model performance that was similar to or better than assimilating either retrieval individually. Comparison of model estimates obtained with global precipitation data and with higher-quality, higher-resolution regional data, respectively, demonstrated that precipitation data quality does determine the overall benefit that can be expected from assimilation. Further work is needed to assess the potentially complementary spatial information that can be derived from retrievals from different frequencies