Search Results (970)

The evaluation of weather forecast accuracy is of major interest in decision making in almost every sector of the economy and in civil protection. To this, a detailed assessment of Bologna Limited-Area Model (BOLAM) seven days fine grid 3 h predictions is made for precipitation, air temperature, relative humidity, and wind speed over a large lowland agricultural area of a Mediterranean-type climate, characterized by hot summers and rainy moderate winters (plain of Arta, NW Greece). Timeseries that cover a four-year period (2016–2019) from seven agro-meteorological stations located at the study area are used to run a range of contingency and accuracy measures as well as Taylor diagrams, and the results are thoroughly discussed. The overall results showed that the model failed to comply with the precipitation regime throughout the study area, while the results were mediocre for wind speed. Considering relative humidity, the results revealed acceptable performance and good correlation between the model output and the observed values, for the early days of forecast. Only in air temperature, the forecasts exhibited very good performance. Discussion is made on the ability of the model to predict major rainfall events and to estimate water budget components as rainfall and reference evapotranspiration. The need for skilled weather forecasts from improved versions of the examined model that may incorporate post-processing techniques to improve predictions or from other forecasting services is underlined. Full article

Estimation of hydrological processes is critical to water resource management, water supply planning, ecological protection, and climate change impact assessment. Mountains in Central Asia are the major source of water for rivers and agricultural practices. The disturbance of mountain forests in the region has altered the hydrological processes and accelerated soil erosion, mudflow, landslides, and flooding. We used the SWAT (Soil and Water Assessment Tool) model calibrated and validated with remote sensing data to quantify the mountainous hydrological processes in the Aktash River watershed (ARW) of Uzbekistan, Central Asia. Simulations showed that the daily surface runoff and streamflow closely responded to daily precipitation. Groundwater discharge reached its maximum in winter because of snowmelt. The wet months were from July to December, and the dry months were from January to June. The magnitudes of the seasonal hydrological processes were in the following order: fall > summer > winter > spring for precipitation and surface runoff; summer > spring > fall > winter for evapotranspiration (ET); winter > spring > fall > summer for snowmelt; fall > winter > summer > spring for water yield and streamflow; and winter > fall > spring > summer for groundwater discharge. The Mann–Kendall statistical test revealed a significant increasing trend for the annual precipitation (τ = 0.45, p < 0.01) and surface runoff (τ = 0.41, p < 0.02) over the past 17 years from 2003 to 2019. Compared to rangeland, forested land decreased monthly and annual average surface runoff by 20%, and increased monthly and annual average groundwater recharge by about 5%. Agricultural land had much higher unit-area values (mm/km²/y) of ET, groundwater recharge, and water yield than those of urban, forest, and range lands. Our research findings provide useful information to farmers, foresters, and decision makers for better water resource management in the ARW, Central Asia, and other mountain watersheds with similar conditions. Full article

In the humid tropics, forest conversion and climate change threaten the hydrological function and stationarity of watersheds, particularly in steep terrain. As climate change intensifies, shifting precipitation patterns and expanding agricultural and pastoral land use may effectively reduce the resilience of headwater catchments. Compounding this problem is the limited long-term monitoring in developing countries for planning in an uncertain future. In this study, we asked which change, climate or land use, more greatly affects stream discharge in humid tropical mountain watersheds? To answer this question, we used the process-based, spatially distributed Soil Moisture Routing model. After first evaluating model performance (Ns = 0.73), we conducted a global sensitivity analysis to identify the model parameters that most strongly influence simulated watershed discharge. In particular, peak flows are most influenced by input model parameters that represent shallow subsurface soil pathways and saturation-excess runoff while low flows are most sensitive to macropore hydraulic conductivity, soil depth and porosity parameters. We then simulated a range of land use and climate scenarios in three mountain watersheds of central Costa Rica. Our results show that deforestation influences streamflow more than altered precipitation and temperature patterns through changes in first-order hydrologic hillslope processes. However, forest conversion coupled with intensifying precipitation events amplifies hydrological extremes, reducing the hydrological resilience to predicted climate shifts in mountain watersheds of the humid tropics. This finding suggests that reforestation can help mitigate the effects of climate change on streamflow dynamics in the tropics including impacts to water availability, flood pulses, channel geomorphology and aquatic habitat associated with altered flow regimes. Full article

A direct way to estimate the likelihood and magnitude of extreme events is frequency analysis. This analysis is based on historical data and assumptions of stationarity, and is carried out with the help of probability distributions and different methods of estimating their parameters. Thus, this article presents all the relations necessary to estimate the parameters with the LH-moments method for the family of distributions defined only by the quantile function, namely, the Wakeby distribution of 4 and 5 parameters, the Lambda distribution of 4 and 5 parameters, and the Davis distribution. The LH-moments method is a method commonly used in flood frequency analysis, and it uses the annual series of maximum flows. The frequency characteristics of the two analyzed methods, which are both involved in expressing the distributions used in the first two linear moments, as well as in determining the confidence interval, are presented. The performances of the analyzed distributions and the two presented methods are verified in the following maximum flows, with the Bahna river used as a case study. The results are presented in comparison with the L-moments method. Following the results obtained, the Wakeby and Lambda distributions have the best performances, and the LH-skewness and LH-kurtosis statistical indicators best model the indicators’ values of the sample (0.5769, 0.3781, 0.548 and 0.3451). Similar to the L-moments method, this represents the main selection criterion of the best fit distribution. Full article

The identification of flood hazards during emerging public safety crises such as hurricanes or flash floods is an invaluable tool for first responders and managers yet remains out of reach in any comprehensive sense when using traditional remote-sensing methods, due to cloud cover and other data-sourcing restrictions. While many remote-sensing techniques exist for floodwater identification and extraction, few studies demonstrate an up-to-day understanding with better techniques in isolating the spectral properties of floodwaters from collected data, which vary for each event. This study introduces a novel method for delineating near-real-time inundation flood extent and depth mapping for storm events, using an inexpensive unmanned aerial vehicle (UAV)-based multispectral remote-sensing platform, which was designed to be applicable for urban environments, under a wide range of atmospheric conditions. The methodology is demonstrated using an actual flooding-event—Hurricane Zeta during the 2020 Atlantic hurricane season. Referred to as the UAV and Floodwater Inundation and Depth Mapper (FIDM), the methodology consists of three major components, including aerial data collection, processing, and flood inundation (water surface extent) and depth mapping. The model results for inundation and depth were compared to a validation dataset and ground-truthing data, respectively. The results suggest that UAV-FIDM is able to predict inundation with a total error (sum of omission and commission errors) of 15.8% and produce flooding depth estimates that are accurate enough to be actionable to determine road closures for a real event. Full article

This study examined the spatiotemporal climate variability over the Ceyhan River basin in Southern Anatolia, Türkiye using historical rainfall and temperature observations recorded at 15 meteorology stations. Various statistical and geostatistical techniques were employed to determine the significance of trends for each climatic variable in the whole basin and its three sub-regions (northern, central, and southern regions). The results revealed that the recent years in the basin were generally warmer compared with previous years, with a temperature increase of approximately 4 °C. The standardized temperature index analysis indicated a shift towards hotter periods after 2005, while the coldest periods were observed in the early 1990s. The spatial distribution of temperature showed non-uniform patterns throughout the basin. The first decade of the study period (1975–1984) was characterized by relatively cold temperatures, followed by a transition period from cold to hot between 1985 and 2004, and a hotter period in the last decade (2005–2014). The rainfall analysis indicated a decreasing trend in annual rainfall, particularly in the northern and central regions of the basin. However, the southern region showed an increasing trend in annual rainfall during the study period. The spatial distribution of rainfall exhibited considerable variability across the basin, with different regions experiencing distinct patterns. The standardized precipitation index analysis revealed the occurrence of multiple drought events throughout the study period. The most severe and prolonged droughts were observed in the years 1992–1996 and 2007–2010. These drought events had significant impacts on water availability and agricultural productivity in the basin. Full article

Urban runoff from the Boat House Creek watershed was suspected as a main delivery mechanism for fecal indicator bacteria (FIB) to the lower White Oak River Estuary in coastal North Carolina, but the dominant source of waste (animal or human) was unknown. Water samples from eight locations within the watershed were collected approximately monthly for two years for enumeration of Escherichia coli (E. coli), enterococci, physicochemical characterization, and microbial source tracking analyses. Concentrations and loadings of E. coli and enterococci were typically elevated during stormflow relative to baseflow conditions, and most samples (66% of enterococci and 75% of E. coli) exceeded the US EPA statistical threshold values. Concentrations of FIB were significantly higher during warm relative to colder months. Human sources of FIB were not observed in the samples, and FIB concentrations increased in locations with wider buffers, thus wildlife was the suspected main FIB source. Stormwater control measures including a rain garden, water control structures, swale modifications, and check dams were implemented to reduce runoff and FIB loadings to the estuary. Stormflow reductions of >5700 m³ year⁻¹ are estimated from the installation of the practices. More work will be needed to improve/maintain water quality as watershed development continues. Full article

MercLok^TM P-640 (MercLok) is a proprietary product developed by Albemarle as a mercury (Hg) treatment technology. MercLok captures mercury and sequesters it for a long period under ambient environmental conditions. For this project, MercLok was applied to Hg-contaminated calcines at two abandoned Hg mine sites in northern California to evaluate its efficacy in rendering such contaminated materials less hazardous and thereby reducing remediation project costs. The first application (Site 1) consisted of two calcines amended with MercLok in isolated reactor buckets under two hydrologic remediation approaches (“repository cap” and “reactive barrier”) while exposed to ambient environmental conditions. Non-amended and amended calcines and their leachates were analyzed for Hg content and related conditions during a five-month study period, demonstrating >95% reduction in leachable Hg. The second application (Site 2) involved full-scale site remediation with the application of both approaches and additional hydrologic controls to minimize run-on, erosion, and runoff. Confirmation sampling and subsequent observations indicate that the amendments and hydrologic controls effectively stabilized the site and minimized Hg releases. These application projects demonstrate the efficacy of MercLok as a component of hydrologic controls for treating Hg-contaminated material to achieve long-term mine site remediation objectives. Full article

Precise estimation of the spatial and temporal characteristics of rainfall is essential for producing the reliable catchment response needed for proper management of water resources. However, in most parts of the world, gauged rainfall stations are sparsely distributed and fail to properly capture the spatial variability of rainfall. Furthermore, the gauged rainfall data can sometimes be of short length or require validation. Following this, we present a procedure that enhances the trustworthiness of gauged rainfall data and the accuracy of the rainfall estimations of five satellite-based precipitation estimate (SPE) products by validating them using the 1779 gauged rainfall stations across Thailand. The five SPE products considered include CMORPH-BLD; TRMM-3B42; CHIRPS; CHIRPS-PL; and TRMM-3B42RT. Prior to validation, the gauged rainfall dataset was verified using double mass curve (DMC) analysis to eliminate questionable and inconsistent readings. This led to the improvement of the Nash–Sutcliffe Efficiency (NSE) between the station of interest and its surroundings by 13.9% (0.758–0.863), together with an average 11.8% increase with SPE products, whilst dropping only 7% of questionable dataset. Three different bias correction (BC) procedures were applied to correct SPE products using gauge-based gridded rainfall (GGR). Once DMC and BC procedures were implemented together, the performance of the SPE products was found to increase significantly. Finally, the application of the ensemble weighted average of the three best-performing bias-corrected SPE products (Bias-CMORPH-BLD, Bias-TRMM-3B42, and Bias-CHIRPS) further enhanced the NSE to 0.907 and 0.880 in calibration and validation time periods, respectively. The proposed DMC-based correction SPE and the weighting procedure of multiple SPE products allows for an easy means of obtaining daily rainfall in remote locations with sufficient accuracy. Full article

The hospitality industry is increasing its awareness of how the integration of nature-based solutions can decrease its environmental impact while maintaining or increasing the service level of the sector. Constructed wetlands (CWs) constitute a promising sustainable solution for proper in situ domestic wastewater treatment. This literature review elucidates the status of CWs implementation in the hospitality industry to help foster the exchange of experiences in the field and deliver examples of approaches in different contexts to support future applications of this technology. Most of the studies reported in the literature were conducted in Europe, but studies emanating from Asia and South America are also available. The design of CWs, the horizontal and vertical subsurface flow CWs (HSFCW, VSFCW), and hybrid systems have been reported. The average removal efficiencies of the systems ranged from 83 to 95% for biochemical oxygen demand, 74 to 94% for chemical oxygen demand, 78 to 96% for total suspended solids, 75 to 85% for ammonium, 44 to 85% for ammonia, 50 to 73% for nitrate, 57 to 88% for total Kjeldahl nitrogen, 51 to 58% total nitrogen, and 66 to 99% for total phosphorus. The majority of the systems were implemented as decentralized treatment solutions using HSFCWs, with the second most common design being the hybrid CW systems in order to reduce area requirements, increase treatment efficiency, and prevent clogging. Overall, CWs are a promising sustainable solution which may support access to adequate sanitation worldwide as well as safe wastewater recycling and reuse, leading to more sustainable tourist destinations. Full article

The research presented herein studies three episodes of flooding that affected the ephemeral basin of the Sant Jordi stream in northwestern Mallorca. These events are considered common since they do not reach the proportions in terms of the flow rates of other cases that have occurred in Mallorca, but they are nevertheless important due to the impact they have on human activity and also due to the morphological changes caused in the basin itself. On the one hand, the development of the field work to characterize and calculate the peak flows is presented, and on the other hand, the geomorphic changes caused by the water and the materials carried away are explained. The results allow us to identify a type of Mediterranean flood, which happens on a regular basis, but which does not stand out for its flows or for its major socio-economic impacts but still has an effect on the natural and anthropic environment. This information can be valuable for local and regional authorities as well as for the public to avoid risk situations and prevent impacts on public and private property caused by future events. Full article

In this study, we present artificial neural networks (ANNs) to aid in a reconnaissance evaluation of an aquifer storage and recovery (ASR) well. Recovery effectiveness (REN) is the proportion of ASR-injected water recovered during subsequent extraction from the same well. ANN-based predictors allow rapid REN prediction without requiring preparation for and execution of solute transport simulations. REN helps estimate blended water quality resulting from a conservative solute in an aquifer, extraction for environmental protection, and other uses, respectively. Assume that into an isotropic homogenous portion of an unconfined, one-layer aquifer, extra surface water is injected at a steady rate during two wet months (61 days) through a fully penetrating ASR well. And then, water is extracted from the well at the same steady rate during three dry months (91-day period of high demand). The presented dimensionless input parameters were designed to be calibrated within the ANNs to match REN values. The values result from groundwater flow and solute transport simulations for ranges of impact factors of unconfined aquifers. The ANNs calibrated the weighting coefficients associated with the input parameters to predict the achievable REN of an ASR well. The ASR steadily injects extra surface water during periods of water availability and, subsequently, steadily extracts groundwater for use. The total extraction volume equaled the total injection volume at the end of extraction day 61. Subsequently, continuing extraction presumes a pre-existing groundwater right. Full article

Climate change is a threat to mining and other industries, especially those involving water supply and management, by inducing or amplifying some climatic parameters such as changes in precipitation regimes and temperature extremes. Using the latest NASA NEX-GDDP-CMIP6 datasets, this study quantifies the level of climate change that may affect the development of two mine sites (site 1 and site 2) in north–east Kazakhstan. The study analyses the daily precipitation and maximum and minimum temperature a of a number of global circulation models (GCM) over three future time periods, the 2040s, 2060s, and 2080s, under two shared socioeconomic pathway (SSP) scenarios, SSP245 and SSP585, against the baseline period 1981–2014. The analyses reveal that: (1) both maximum and minimum temperature will increase under both SSP in those time periods, with the rate of change for minimum temperature being higher than maximum temperature. Minimum temperature, for example, will increase by 2.2 and 2.7 °C under SSP245 and SSP585, respectively, over the 2040s period at both sites; (2) the mean annual precipitation will increase by an average rate of 7% and 10.5% in the 2040s for SSP245 and 17.5% and 7.5% for SSP585 in the 2080s at site 1 and site 2, respectively. It is also observed that summer months will experience drier condition whilst all other months will increase in precipitation; (3) the values of 24 h precipitation with a 10 year return period will also increase under both SSP scenarios and future time periods for most of the studied GCM and at both mine sites. For instance, over the near future period, a 6.9% and 2.8% increase in 10 year 24 h precipitation is expected to happen over site 1 and site 2, respectively, under SSP245. These predicted changes should be considered as design criteria adjustments for projected water supply and water management structures. Full article

Green roofs have been used to reduce rainfall runoff by altering hydrological processes through plant interception and retention as well as detention within the green roof system. Green roof media depth, substrate type, plant type and density, regional climatic conditions, rainfall patterns, and roof slope all impact runoff retention. To better understand the impacts of media depth (10, 15, and 20 cm), plant (planted and non-planted), and rainfall pattern (low, medium, and high) on rainfall retention, we analyzed data collected between September 2005 and June 2008 from 24 green roof models (61 cm × 61 cm) for growing and non-growing seasons. Our results showed that a planted green roof has greater rainfall retention capability than a non-planted green roof for all media depths. Interestingly, a non-planted green roof system with a 10 cm media depth retained greater rainfall than a planted green roof during both growing and non-growing periods. Retention capability decreased with increasing rainfall amounts for both planted and non-planted green roofs and seasons (growing and non-growing). The 15 cm media depth green roof retained significantly greater rainfall depth than the 20 cm models during medium (0.64 to 2.54 cm) and high (>2.54 cm) rainfall events for the growing season but not during the non-growing season. The study provides insight into the interactive effects of media depth, rainfall amount, plant presence, and seasons on green roof performance. The results will be helpful for designing economical and effective green roof systems. Full article

Most of the studies on rainwater harvesting analysis present the outcomes for particular cities, representing a single set of results for a specific city. However, in reality, significant spatial and weather variabilities may exist, due to which presenting only one set of results for a particular city would be misleading. This paper presents the potential weather and spatial variabilities on the expected water savings and supply reliability through the domestic rainwater tank for an inland city. An earlier-developed daily water balance model, eTank, was used for the calculations of annual water savings and reliability. An Australian inland city, Canberra, was selected as a case study and relevant daily rainfall data were collected from the Australian Bureau of Meteorology website. For the analysis of spatial variation, two rain gauge stations within the city of Canberra were selected. For each station, from the historical data, three years were selected as dry, average and wet years. For each weather condition, annual water savings and reliabilities were calculated for different demands with different tank sizes up to 10,000 L connected with different roof sizes. Then, variations in annual water savings and reliabilities among different weather conditions, as well as among different stations, were evaluated. It was found that, with regard to annual water savings, a maximum variation of 68.6% can be expected between dry and wet weather; however, only a 15.4% maximum spatial variation is expected among the selected stations. Regarding reliability, a maximum variation of 123% is expected between dry and wet weather. Whereas, only a 17% spatial variation is expected among the selected stations. Such a study will provide valuable insights for rainwater tank users and stakeholders on potential variabilities due to weather and spatial differences. Full article