To proper manage water resources a key component is the data acquisition through environmental monitoring. A field monitoring allows us to identify changes that may occur in the hydrological regime as a result of climate change and land use and occupation. However, the cost of sophisticated hydrological monitoring equipment’s may be prohibitive for many locations around the world. This work aims to develop a low-cost monitoring platform (LCMP) to be used to densify the hydrological monitoring network for rainfall, small rivers level and water temperature. We started the process by building an open source environmental data collection platform based on the Arduino electronic platform associated with low-cost sensors, GSM shield, a solar panel and a battery. The first step was to test data transmission to a data server through the GPRS network, which worked as expected, just like platforms using professional modems. The second step was the evaluation of the reliability and quality of data for precipitation and water temperature measurements. For precipitation a low-cost tipping bucket rain gauge was used and for temperature low cost sensors (DS18B20) were used. Those sensors were compared to a professional monitoring platform used for official hydrological monitoring. We identified an excellent correlation between both, with coefficient of determination greater than 0.99. The LCNP was kept activated and collecting data for over 150 days without major problems. The cost of the professional solution currently used is close to € 8,200 while the low-cost solution resulted in € 450, approximately, 5.5% of the cost of the professional solution. The next important steps are to validate the level sensor reliability and assess the LCNP durability exposed to weather conditions.

One of the challenges to managing water resources and understanding their sources is the heterogeneity created by interactions among hydrological, ecological and anthropological processes and how it is best characterized. An option recently applied to other scientific disciplines is identifying and analyzing the emergent phenomena of complex systems or networks, which are far from equilibrium and whose components self-organize into novel structures/processes via their collective interactions with each other and the environment. A new level of organization and complexity emerges that cannot be predicted from or attributed to the components alone. Deriving predictions based on functionally emergent properties (top-down) of watershed systems differs considerably from making predictions based on reductionist models (bottom-up) of those systems.

River networks have been shown to function as hierarchically nested processes from which stability emerges as a property that buffers variation and extreme events. It is the connectivity and interactions (over a range of spatiotemporal scales) among geomorphic and hydrologic components of watersheds or river networks that give rise to the emergent properties. There are a number of statistical and representative sampling techniques available to identify and quantify component connectivity, the importance of which is exemplified by the extent to which connectivity affects the way that rainfall events alter moisture, heat and carbon fluxes associated with drought. In essence, events transmit information through connected components of watersheds, such that accrued information is at the root of a system’s emergent properties. This presentation highlights some of the ways that emergent properties, which have been influential in expanding the perspectives applied to other sciences, are now being applied to water resources and the associated systems.

The paper presents the results of observations of the spatial variability of the chemical composition of the river Modonkul. According to these observations, the chemical composition of the water changes from bicarbonate calcium-magnesium in the upper part of the river through sulfate-calcium-sodium (and other transitional differences to sulfate-calcium-magnesium type) in the river's mouth. Redistribution of dissolved and suspended forms of migration of heavy metals occurs in the alkaline environment in river Modonkul. The data of the content of rare earth elements in water river are obtained.

Global Climate Model (GCM) downscaling projections of climate is important for future impact of climate change. The impact of climate change on the precipitation is studied from literature, modeling, and observations. The rainfall trend in this research was examined across the country using Global Climate Model (GCM) data from period of 1978 to 1999. Downscaling was done on the basis of ascertained relationships between historical observed precipitation records from 36 stations of Pakistan Meteorological Department (PMD). Mann-Kendall test and Taylor Diagrams were used to analyze the data. All of the selected precipitation products were validated at monthly, seasonal and annual time scales utilizing PMD data. The outcomes illustrated that: (1) the precipitation estimates from MIROC, ECHAM and CanESM products correlated well with the referenced PMD observations at monthly time scale. (2) Compared to the MIROC and CanESM, the precipitation estimates from ECHAM were more consistent in all seasons mainly in the winter season with lowest relative bias (2.61%) and highest Correlation Coefficient (0.92); (3) ECHAM showed an apparent dominance over MIROC and CanESM products in order to detain spatial distribution of precipitation over Pakistan. The results exposed a declining trend (-1.18 mm/decade) over southern part of the country, while northern area showed growing trends. The diminishing trend may be featured to the existence of drought period for next few years in various part of country. The results also indicate spatial and temporal change in precipitation.

Quantifying groundwater resources is an important issue for effective water resource planning and management at river basin scale and it has to take into account all the natural and anthropogenic components of the water balance, i.e.: rainfall and runoff processes, as well as mutual interactions between surface water and groundwater, but also artificial groundwater recharges (i.e. from irrigation) and groundwater extractions.

Here, a DEM-based methodology is applied to the case study of northern Etna groundwater system and Alcantara river basin. This method, also known as reverse hydrogeological balance method, allows us to estimate the active mean annual recharge based on precipitation, temperature and potential evapotranspiration in the area.

The main objective of this study is to quantify how the DEM resolution influences the groundwater resource estimation through the above-mentioned methodology and how this is also influenced by the method for potential evapotranspiration assessment.

Groundwater and surface flow for our case study have been evaluated for 5 different DEM resolutions (20, 60, 100, 300, 500 meters) and with 3 different theoretical approaches for evapotranspiration calculation (Turc Method, Modified-Turc Method, and Budyko Method).

Results are validated against isochronous recorded data of river discharge at Moio Alcantara cross-section and show how the reverse hydrogeological balance method shows better performances if implemented with the Budyko Method for estimating evapotranspiration and by using a DEM with 60x60m grid resolution.

The available water volume of Lake Ziway in Ethiopia is declining at an alarming rate which hinders the lake services for a wide variety of sectors. However, there is a lack of systematic study to evaluate the contribution of water withdrawal by various sectors to the decline in the lake actual storage. In the present study, we conducted a Water Abstraction Survey (WAS) to estimate actual water withdrawal from the lake and a water balance model to evaluate the isolated impact of water withdrawal on the lake water volume and level. The likely impact of three development pathways on the lake storage and water level was assessed. Results indicate that the existing water withdrawal for irrigation has significantly contributed to the change in the actual storage of Lake Ziway. When the future development plans are fully implemented, the annual amount of irrigation water withdrawal from the lake will be 94 Mm³. This will cause the lake water level to drop by 0.94 m, which translates to 38 km² reduction in the lake surface area. Consequently, the lake will lose 26% of its actual storage volume. Hence, the current impact of water resources development around the lake is substantially large and will exacerbate in the future. This calls serious action on the management of water abstraction from the lake.

The Water Framework Directive (WFD) requires from member states to monitor hydromorphological features of rivers in order to assess their ecological quality. Thus, numerous hydromorphological assessment methods have been developed with most of them focusing on the dynamics of hydrology, geomorphology and riparian zone extent. Within the scope of this study, we assessed the hydromorphological features of more than 100 river reaches distributed among fourteen WFD River Basin Districts (RBDs) to identify the main drivers of hydromorphological perturbation. We employed the River Habitat Survey (RHS) and we recorded hydromorphological features and modifications in both banks and the channel bed along 500 m for each reach. Then, the Habitat Modification Score (HMS) and the individual sub-scores that indicate the extent of specific modifications (e.g. bridges, fords, weirs, bank reprofiling, bank reinforcement etc) were calculated in order to a) assess the severity of the total artificial modification and b) to highlight the most common and severe causes of longitudinal and cross-sectional alterations. The results showed that alterations such as reprofiling and reinforcement of banks, contributed the most to the total HMS followed by the presence of bridges. Particularly the bank alterations indicate a serious deterioration of the longitudinal profile of the reaches while the occurrence of many small and larger bridges is the main cause for perturbations that affect the stream cross-sectional profile. Overall, these results compile a first nationwide assessment of the hydromorphological status of Greek rivers in line with the WFD and set the basis for further research that will focus on the diversity of stream habitat features as a measure for the overall ecological quality.

With the growing concerns over emerging contaminants in indirect potable reuse (IPR) applications, we investigate the impact on human health risk of emerging contaminants introduced into groundwater. Some emerging contaminants have potential endocrine-related health effects at a specific exposure range that is much lower than current guidelines. We start by analyzing Bisphenol A (BPA), which is one of the frequently detected emerging contaminants in groundwater. The objective of this study is to understand how the non-trivial toxicity of BPA affects the estimation of human health risks and, consequentially, aquifer resilience. Based on our results, we aim to provide indications on how to improve water resources management in BPA contaminated sites. We use numerical methods to model BPA contamination of a three-dimensional aquifer, and human health risks and aquifer resilience are estimated at a control plane representing an environmentally sensitive target. A Monte Carlo simulation is conducted to compute uncertainty associated with two levels of heterogeneity. In order to evaluate health risks due to BPA, two types of Dose-Response (DR) models are considered: the monotonic DR model for general exposure and the non-monotonic DR model for prenatal/postnatal exposure. The aquifer resilience is defined as the capacity to recover the state where water is considered potable (i.e., negligible health risks due to BPA). When using the non-monotonic DR model, computational results indicate that the aquifer resilience (reduces) decreases and its uncertainty increases as the aquifer heterogeneity increases. On the other hand, the aquifer resilience considering the monotonic DR model (enhances) increases, and its uncertainty increases relatively smaller than the one considering the non-monotonic DR model. In addition, the variability of the aquifer resilience is controlled by the residence time of the BPA plumes at the control plane, which is related to the volumetric flow rate at the front side of the contamination source. Finally, the decision making strategy for BPA contaminated sites should be established in accordance with the heterogeneous structure of aquifer and land uses that determine which DR model of BPA is more important in estimating the aquifer resilience.

In water resources management, remote sensing data and techniques are essential in watershed characterization and monitoring, especially when no data are available. Water quality is usually assessed through in-situ measurements which require high cost and time. Water quality parameters help in decision making regarding the further use of water-based on its quality. Turbidity is an important water quality parameter and an indicator of water pollution. In the past few decades, remote sensing has been widely used in water quality research.

In this study, we compare turbidity parameters retrieved from high-resolution image with in-situ measurements collected from Borabey Lake, Turkey. Here the use of RapidEye-3 images (5 m-resolution) allows for a detailed assessment of spatio-temporal evaluation of turbidity, through the Normalized Difference Turbidity Index (NDTI). The turbidity results were then compared with data from twenty-one in-situ measurements collected at the same period. The actual water turbidity measurements showed high correlation with the estimated NDTI mean values with an R² of 0.84. The research findings support the use of remote sensing data of RadipEye-3 to estimate water quality parameters in small water areas. For future studies, we recommend investigating different water quality parameters using high-resolution remote sensing data.

Solute transport in groundwater is characterized by a high level of uncertainty since it is impossible to completely measure the spatial distribution of key soil properties, such as the hydraulic conductivity. Several studies have shown how an heterogeneous hydraulic conductivity field may lead to the formation of preferential channels (or high conductivity channels) in which the solute flows. Given a realization of the hydraulic conductivity field, it is possible to estimate the location of preferential channels using a graph-theory based method. The minimum hydraulic resistance and least resistance path are efficiently computed, so that these metrics can be effectively employed to assess the uncertainty of preferential flows using computationally intensive stochastic methods, such as Monte-Carlo simulations. For example, these metrics can be used for site characterization, choosing locations where to sample the hydraulic conductivity in order to reduce the uncertainty of high conductivity channels. As a consequence, our preliminary studies displayed more than 40% reduction on first arrival time uncertainty, when compared to a regular grid sampling protocol with the same number of sampling locations. The iterative sampling strategy can be reproduced using LazyMole, an open-source tool implementing the algorithms to compute the minimum hydraulic resistance and least resistance path for a given hydraulic conductivity field.