Garantizar la calidad del agua potable es indispensable para cualquier sistema de tratamiento, especialmente en una mega ciudad como Bogotá, por este motivo se desarrollaron modelos ARIMA que permiten pronosticar el comportamiento temporal de la calidad del agua del embalse San Rafael y la potabilizadora Francisco Wiesner. Para este fin se seleccionaron tres estaciones de macromedición dentro del sistema Chingaza, estas fueron: Río Teusacá–Salitre, embalse San Rafael y suministrada CDC. Se eligieron los parámetros indicadores de calidad del agua más pertinentes para la investigación, y mediante un tratamiento estadístico se completaron datos faltantes de las series de tiempo diarias entre los años 2008–2015. Para generar los modelos ARIMA, en tres escalas de tiempo (Diario, media móvil semanal y media móvil mensual), se utilizó el software IBM-SPSS y su herramienta modelizador experto; debido a que los valores de los estadísticos relevantes de los modelos no cumplieron con los rangos sugeridos en la literatura consultada, se decidió emplear el proceso iterativo de Box-Jenkins adaptado por Pérez (2005) para estimar modelos más ajustados. Se realizó una correlación entre los parámetros indicadores de las estaciones seleccionadas, detectando características diferenciales en cada una de las estaciones. De igual manera se analizaron los costos y cantidades de los productos químicos utilizados en la planta potabilizadora, verificando la relación directa entre la variación de las características de calidad del agua y el uso de dichos productos. Adicionalmente, se realizó el cálculo del IRCA y el análisis de los valores que infringieron la normatividad nacional, evidenciando una óptima calidad del recurso hídrico que se distribuye a los beneficiarios del sistema potabilizador. Finalmente, se utilizó la metodología del marco lógico para formular estrategias sustentables que optimicen la operación de la PTAP Francisco Wiesner y aseguren la calidad del agua de abastecimiento para Bogotá. | Secure the quality of drinking water is essential for any treatment system, especially in a megacity like Bogotá, for this reason, ARIMA models were developed that allow predicting the temporal behavior of the water quality of the San Rafael reservoir and the Francisco Wiesner drinking water treatment plant. For this purpose, three metering stations were selected in the Chingaza system, these were: Río Teusacá–Salitre, embalse San Rafael y suministrada CDC. The water quality indicator parameters most pertinent to the research were chosen, and through of statistical treatment, missing data from the daily time series were completed between the years 2008 2015. To generate the ARIMA models, in three time scales (Daily, weekly moving average and monthly moving average), the IBM-SPSS software and its expert modeler tool were used; due to the fact that the values of the relevant statistics of the models did not comply with the ranges suggested in the literature consulted, it was decided to use the Box-Jenkins iterative process adapted by Pérez (2005) to estimate more adjusted models. A correlation was made between the indicator parameters of the selected stations, detecting differential characteristics in each of the stations. In the same way, the costs and quantities of the chemical products used in the water treatment plant were analyzed, verifying the direct relationship between the variation of water quality characteristics and the use of said products. Additionally, the calculation of the IRCA and the analysis of the values that violated the national regulations were made, evidencing an optimum quality of the water resource that is distributed to the beneficiaries of the water treatment system. Finally, the logical framework approach was used to formulate sustainable strategies that optimize the operation of the Francisco Wiesner water treatment plant and ensure the water quality for Bogotá. | Empresa de Acueducto y Alcantarillado de Bogotá

Los modelos de simulacion al considerar procesos basicos de la planta y como ellos son influenciados por el ambiente, tienen la ventaja de representar una economia de tiempo y recursos en la investigacion basica de evaluacion de rendimiento y zonificacion de cultivos, constituyendo un avance tecnologico de gran ayuda para la agilizacion del proceso de tranferencia en el campo de la produccion agricola. El presente trabajo forma parte de un proyecto de investigacion mas amplio sobre aplicabilidad del Modelo Ceres/Maiz, y aqui se presentan los resultados correspondientes al componente del balance de agua del Modelo Ceres/Maiz, en dos perfiles de suelos de texturas contrastantes. Adicionalmente se incluye informacion complementaria sobre descripcion del perfil, densidad aparente, caracterizacion de raices y determinacion de curvas caracteristicas de humedad para ambos suelos. Finalmente se comparan los parametros de humedad del Modelo Ceres/Maiz: limite superior de humedad, limite inferior de humedad, el coeficiente de drenaje y el porcentaje de humedad a saturacion para ambos perfiles y se senalan las principales dificultades en la determinacion de los mismos.

Monthly time series, from 2001 to 2016, of the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) from MOD13Q1 products were analyzed with Seasonal Trend Analysis (STA), assessing seasonal and long-term changes in the mangrove canopy of the Teacapan-Agua Brava lagoon system, the largest mangrove ecosystem in the Mexican Pacific coast. Profiles from both vegetation indices described similar phenological trends, but the EVI was more sensitive in detecting intra-annual changes. We identified a seasonal cycle dominated by Laguncularia racemosa and Rhizophora mangle mixed patches, with the more closed canopy occurring in the early autumn, and the maximum opening in the dry season. Mangrove patches dominated by Avicennia germinans displayed seasonal peaks in the winter. Curves fitted for the seasonal vegetation indices were better correlated with accumulated precipitation and solar radiation among the assessed climate variables (Pearson’s correlation coefficients, estimated for most of the variables, were r ≥ 0.58 p < 0.0001), driving seasonality for tidal basins with mangroves dominated by L. racemosa and R. mangle. For tidal basins dominated by A. germinans, the maximum and minimum temperatures and monthly precipitation fit better seasonally with the vegetation indices (r ≥ 0.58, p < 0.0001). Significant mangrove canopy reductions were identified in all the analyzed tidal basins (z values for the Mann-Kendall test ≤ −1.96), but positive change trends were recorded in four of the basins, while most of the mangrove canopy (approximately 87%) displayed only seasonal canopy changes or canopy recovery (z > −1.96). The most resilient mangrove forests were distributed in tidal basins dominated by L. racemosa and R. mangle (Mann-Kendal Tau t ≥ 0.4, p ≤ 0.03), while basins dominated by A. germinans showed the most evidence of disturbance.

Gravity Recovery and Climate Experiment (GRACE) derived groundwater storage (GWS) data are compared with in-situ groundwater levels from five groundwater basins in Jordan, using newly gridded GRACE GRCTellus land data. It is shown that (1) the time series for GRACE-derived GWS data and in-situ groundwater-level measurements can be correlated, with R ² from 0.55 to 0.74, (2) the correlation can be widely ascribed to the seasonal and trend component, since the detrended and deseasonalized time series show no significant correlation for most cases, implying that anomalous signals that deviate from the trend or seasonal behaviour are overlaid by noise, (3) estimates for water losses in Jordan based on the trend of GRACE data from 2003 to 2013 could be up to four times higher than previously assumed using estimated recharge and abstraction rates, and (4) a significant time-lagged cross correlation of the monthly changes in GRACE-derived groundwater storage and precipitation data was found, suggesting that the conventional method for deriving GWS from GRACE data probably does not account for the typical conditions in the study basins. Furthermore, a new method for deriving plausible specific yields from GRACE data and groundwater levels is demonstrated.

This study examined the relative importance of climate change and drinking-water treatment for gastrointestinal illness incidence in children (age <5 years) from period 2046–2065 compared to 1991–2010. The northern Wisconsin (USA) study focused on municipalities distributing untreated groundwater. A time-series analysis first quantified the observed (1991–2010) precipitation and gastrointestinal illness associations after controlling for seasonality and temporal trends. Precipitation likely transported pathogens into drinking-water sources or into leaking water-distribution networks. Building on observed relationships, the second analysis projected how climate change and drinking-water treatment installation may alter gastrointestinal illness incidence. Future precipitation values were modeled by 13 global climate models and three greenhouse-gas emissions levels. The second analysis was rerun using three pathways: (1) only climate change, (2) climate change and the same slow pace of treatment installation observed over 1991–2010, and (3) climate change and the rapid rate of installation observed over 2011–2016. The results illustrate the risks that climate change presents to small rural groundwater municipalities without drinking water treatment. Climate-change-related seasonal precipitation changes will marginally increase the gastrointestinal illness incidence rate (mean: ∼1.5%, range: −3.6–4.3%). A slow pace of treatment installation somewhat decreased precipitation-associated gastrointestinal illness incidence (mean: ∼3.0%, range: 0.2–7.8%) in spite of climate change. The rapid treatment installation rate largely decreases the gastrointestinal illness incidence (mean: ∼82.0%, range: 82.0–83.0%).

Freshwater–saline water interactions were evaluated in a coastal region influenced by external forces including tidal fluctuations and seasonal rainfall variations. Five different coastal zones were considered on Jeju Island, South Korea, and electrical conductivity (EC) profiles from the monitoring wells were examined to identify the configuration of the freshwater–saline water interface. There appeared to be discrepancies among EC profiles measured at different points in time. To analyze the dynamic behavior of freshwater–saline water interactions, groundwater level measurements and multi-depth EC and temperature probes were used to obtain time-series data; the data showed that water level, EC and temperature were influenced by both tidal fluctuations and heavy rainfall. The effects of oceanic tide on EC and temperature differed with depth due to hydraulic properties of geologic formations. A spectral filter was used to eliminate the effects of tidal forces and provide information on the influence of heavy rainfall on water level, EC and temperature. Heavy rainfall events caused different patterns and degrees of variation in EC and temperature with depth. The time-series data of EC and temperature in the subsurface at various depths enable greater understanding of the interaction processes between fresh and saline water.

The links between climate variability, depicted by time series of oceanic indices, and changes in total water and groundwater storage are investigated across nine large aquifer basins of the African continent. The Gravity Recovery and Climate Experiment (GRACE) mission’s observations represent a remarkable tool that can provide insight into the dynamics of terrestrial hydrology in areas where direct in situ observations are limited. In order to evaluate the impact of interannual and multidecadal climate variability on groundwater resources, this study assesses the relationship between synoptic controls on climate and total water storage estimates from (i) GRACE from 2002 to 2013 and (ii) a two-variable climate-driven model that is able to reconstruct past storage changes from 1982 to 2011. The estimates are then compared to time series of groundwater levels to show the extent to which total water storage covaries with groundwater storage. Results indicate that rainfall patterns associated with the El Niño Southern Oscillation (ENSO) are the main driver of changes in interannual groundwater storage, whereas the Atlantic MultiDecadal Oscillation (AMO) plays a significant role in decadal to multidecadal variability. The combined effect of ENSO and AMO could trigger significant changes in recharge to the aquifers and groundwater storage, in particular in the Sahel. These findings could help decision-makers prepare more effective climate-change adaptation plans at both national and transboundary levels.

High-frequency time series analysis and cross-correlation identified the relationship between precipitation and water-level responses at 16 sandstone wells in southern California, USA. The time series analysis suggested that the water table rises only when a threshold value of precipitation is reached during the rainy season that likely represents the water content deficit from the previous 7-month dry season being replenished before generating a water-table response. The cross-correlation indicates two statistically significant lag-times: 0–3 and 20–50 days. Confidence in these results was augmented by unprecedented and exceptionally high-resolution sampling frequency. Water pressure readings were collected every second and then analyzed to identify and remove the effects of barometric pressure changes, Earth tides and earthquakes on water levels. These effects are usually considered “noise” in recharge studies, but their accurate quantification helped assess the unconfined nature of the wells, minimize uncertainties of the results, and isolate the groundwater responses to precipitation. Diffusivity values for the thick unsaturated zone, based on the time lags, suggest quick responses are related to flow through fractures and longer time lags are associated with piston-type movement in the matrix. Fast responses were more likely for shallow water tables in response to high-intensity precipitation events and vice versa. These findings are consistent with those found, using lower resolution data, for the Chalk aquifer in England (UK), despite the contrasting fracture and matrix properties, hydrogeological setting and climatic conditions. Thus, the same style of response to precipitation is expected globally where similar fractured porous media are present.

Drought and water scarcity can significantly impair the sustainable development of groundwater resources, a scenario commonly found in aquifers in the Mediterranean region. Water management measures to address these drivers of groundwater depletion are highly relevant, especially considering the increasing severity of droughts under climate change. This study evaluates the potential of managed aquifer recharge (MAR) to offset the adverse effects of drought and water scarcity on groundwater storage. Los Arenales aquifer (central Spain), which was unsustainably exploited for irrigation in the second half of the twentieth century, is employed as a case study. Two neighbouring zones within this aquifer are contrasted, namely, Los Arenales (LA) and Medina del Campo (MC). The primary difference between them in terms of water resources management is the wide-scale implementation of MAR systems in LA since the early 2000s. Several groundwater statistical methods are used. Groundwater-level trend analysis and average piezometric levels show in LA a faster recovery of aquifer storage and less susceptibility to drought compared to MC. On the other hand, standardised precipitation indexes and standardised groundwater level indexes of detrended groundwater-level time series, which do not include the effects of MAR, show that LA can be more negatively affected by drought and groundwater abstraction. The sharper recovery of piezometric levels in LA when considering MAR, and bigger drought impacts observed when the effects of this measure are removed, demonstrate that MAR can effectively alleviate the impacts of water scarcity and drought, providing an adaptation solution to climate change worldwide.

Karst aquifers in subtropical regions are characterized by high variability of water availability and quality due to changes associated with rainy and dry seasons. An additional challenge for water management is the combination of surface-water and karst groundwater systems since high spatiotemporal dynamics cause high variability of water quality. In these cases, adapted protection strategies are required. In this study, a protection approach for the catchment of a river-water diversion point in a rural area in northern Vietnam is developed. The variability of water quality was evaluated by rainy and dry season synoptic surveys of suspended particles and microbial contamination at 49 sites and time series at three sets of paired sites under constant hydraulic conditions. The anthropogenic land-use activities in the catchment were mapped to identify potential contamination sources and to highlight the challenging combination of surface-water and karst groundwater management. The analyzed data indicate differences in water quality between the dry and rainy seasons and a higher influence on water quality from land use than from hydrologic conditions. Furthermore, the results suggest a high risk of contamination resulting from residential areas, agriculture, and livestock farming, and reveal the necessity of implementation of appropriate measures such as restricted farming and the hook-up of buildings to municipal sewage disposal. Finally, the data show that water quality can be improved by adjusting water withdrawals by the time of day. The applied methods can be transferred to other surface-water and karst groundwater systems in similar subtropical environments.