Hydrology, Volume 11, Issue 6 (June 2024) – 11 articles

We assessed and quantified future projected changes in terrestrial evaporative demand by calculating Potential Evapotranspiration (PET) for the North American Monsoon region in the Southwestern U.S. and Mexico. The PET projections were calculated using the daily Penman–Monteith equation. The terrestrial meteorological variables needed for the equation (i.e., minimum and maximum daily temperature, specific humidity, wind speed, incoming shortwave radiation, and pressure) were obtained from the North American–CORDEX initiative. We used dynamically downscaled projections of three CMIP5 GCMs for RCP8.5 emission scenarios (i.e., HadGEM2-ES, MPI-ESM-LR, and GFDL-ESM2M), and each was dynamically downscaled to ~25 km by two RCMs (i.e., WRF and regCM4). All terrestrial annual PET projections showed a statistically significant increase when comparing the historical period (1986–2005) to future projections (2020–2039 and 2040–2059). The regional spatial average of the six GCM-RCM combinations projected an increase in the annual PET of about +4% and +8% for 2020–2039 and 2040–2059, respectively. The projected average 20-year annual changes over the study area range for the two projection periods were +1.4%–+8.7% and +3%–+14.2%, respectively. The projected annual PET increase trends are consistent across the entire region and for the six GCM-RCM combinations. Higher annual changes are projected in the northeast part of the region, while smaller changes are projected along the pacific coast. The main drivers for the increase are the projected warming and increase in the vapor pressure deficit. The projected changes in PET, which represent the changes in the atmospheric evaporative demand, are substantial and likely to impact vegetation and the hydrometeorological regime in the area. Quantitative assessments of the projected PET changes provided by this study should be considered in upcoming studies to develop resilience plans and adaptation strategies for mitigating the projected future changes. Full article

This research aimed to analyze the relationship between deforestation (DFT) and climatic variables during the rainy (CHU+) and less-rainy (CHU−) seasons in the Tapajós River basin. Data were sourced from multiple institutions, including the Climatic Research Unit (CRU), Center for Weather Forecasts and Climate Studies (CPTEC), PRODES Program (Monitoring of Brazilian Amazon Deforestation Project), National Water Agency (ANA) and National Centers for Environmental Prediction/National Oceanic and Atmospheric Administration (NCEP/NOAA). The study assessed anomalies (ANOM) in maximum temperature (TMAX), minimum temperature (TMIN) and precipitation (PREC) over three years without the occurrence of the El Niño–Southern Oscillation (ENSO) atmospheric–oceanic phenomenon. It also examined areas with higher DFT density using the Kernel methodology and analyzed the correlation between DFT and climatic variables. Additionally, it assessed trends using the Mann–Kendall technique for both climatic and environmental data. The results revealed significant ANOM in TEMP and PREC. In PREC, the highest values of ANOM were negative in CHU+. Regarding temperature, the most significant values were positive ANOM in the south, southwest and northwestern regions of the basin. Concerning DFT density, data showed that the highest concentration was of medium density, primarily along the highways. The most significant correlations were found between DFT and TEMP during the CHU− season in the Middle and Lower Tapajós sub-basins, regions where the forest still exhibits more preserved characteristics. Furthermore, the study identified a positive trend in TEMP and a negative trend in PREC. Full article

In this study, we performed a preliminary soil analysis and collected environmental data for the Dulcepamba River Basin in Bolivar–Ecuador, before carrying out its hydrological restoration (HR). A geographic information system (GIS) and the multicriterion Analytical Hierarchy Process (AHP) decision-making method were used. The comprehensive evaluation included morphological aspects, soil properties, climatic conditions, vegetation, and land use. The terrain conditions were investigated using indicators such as the flow capacity, topographic moisture, soil resistance, sediment transport, current density, curve number, NDVI, precipitation, and distance to rivers. The results and analysis are presented in a series of maps, which establish a starting point for the HR of the Dulcepamba watershed. The key factors for assessing soil degradation in the watershed include land use, vegetation cover, sedimentation, humidity, and precipitation. Of the studied territory, 10.7 do not require HR, while 20.28% demand HR in the long term. In addition, 30.67% require HR in the short term, and 33.35% require HR immediately. Based on the findings, it is suggested that authorities consider the environmental remediation of the watershed and propose various HR measures. This analytical approach could prove valuable as a tool for the environmental restoration of watersheds in Ecuador. Full article

Cutting-edge technology for fluvial monitoring has revolutionised the field, enabling more comprehensive data collection, analysis, and interpretation. Traditional monitoring methods were limited in their spatial and temporal resolutions, but advancements in remote sensing, unmanned aerial systems (UASs), and other innovative technologies have significantly enhanced the fluvial monitoring capabilities. UASs equipped with advanced sensors enable detailed and precise fluvial monitoring by capturing high-resolution topographic data, generate accurate digital elevation models, and provide imagery of river channels, banks, and riparian zones. These data enable the identification of erosion and deposition patterns, the quantification of sediment transport, the evaluation of habitat quality, and the monitoring of river flows. The latter allows us to understand the dynamics of rivers during various hydrological events, including floods, droughts, and seasonal variations. This manuscript aims to provide an update on the main research themes and topics in the literature on the use of UASs for river monitoring. The latter is achieved through a bibliometric analysis of the publication trends and identifies the field’s key themes and collaborative networks. The bibliometric analysis shows trends in the number of publications, number of citations, top contributing countries, top publishing journals, top contributing institutions, and top authors. A total of 1085 publications on UAS monitoring in rivers are identified, published between 1999 and 2023, showing a steady annual growth rate of 24.44%. Bibliographic records are exported from the Web of Science (WoS) database using a comprehensive set of keywords. The bibliometric analysis of the raw data obtained from the WoS database is performed using the R software. The results highlight important trends and valuable insights related to the use of UASs in river monitoring, particularly in the last decade. The most frequently used author keywords outline the core themes of UASs monitoring research and highlight the interdisciplinary nature and collaborative efforts within the field. “River”, “topography”, “photogrammetry”, and “Structure-from-Motion” are the core themes of UASs monitoring research. These findings can guide future research and promote new interdisciplinary collaborations. Full article

A univariate analysis that relies solely on precipitation data in low flow frequency analysis is a technique to express meteorological drought, so it is limited to analyzing the characteristics of hydrological drought related to available water resources. In addition, if the data for the model calibration are insufficient, the uncertainty of a single variable limits the construction of a reliable model. To improve this problem, a frequency analysis was performed by constructing a bivariate copula model as a multivariate model with a high correlation between variables targeting reservoir inflows. The methodology utilizes the theory of runs to identify low flow events, establishing a threshold based on the mandatory regional water supply plan, and determining the low flow duration and cumulative water deficit. The Gumbel copula function, effective in capturing correlations between hydrological variables, was applied to derive a joint bivariate probability distribution, facilitating the calculation of combined low flow event return periods. This study compared low flow frequencies at Soyanggang dam (’74–’22) and Chungju dam (’86–‘22), which are in the same Han River basin but have different capacities and water demands, using a bivariate copula model. The top four extreme low flow events for the two adjacent dam basins did not occur in the same year and, in the years of the extreme low flow events at one of the two dam basins, there was an insignificant magnitude at the remaining dam basin. This result is noteworthy because it shows that the possibility of extreme low flow events appearing simultaneously in both watersheds is not as high as expected. The operational efficiency can be improved by setting the coordinated operation rules of the two reservoirs using the copula dependency structure. Full article

The physical integrity of the Ngerengere River and its three tributaries drains within Morogoro Municipality were evaluated by assessing the variations in land-use–land cover (LULC) in the river’s buffer zone, the discharge, and the contamination of river water and sediment from nutrients and heavy metals. Integrated geospatial techniques were used to classify the LULC in the river’s buffer zone. In contrast, the velocity area method and monitoring data from the Wami-Ruvu Basin were used for the discharge measurements. Furthermore, atomic absorption spectrophotometry was used during the laboratory analysis to determine the level of nutrients and heavy metals in the water and river sediment across the 13 sampling locations. The LULC assessment in the river’s buffer during the sampling year of 2023 showed that bare land and built-up areas dominate the river’s buffer, with a coverage of 28% and 38% of the area distribution. The higher discharge across the sampling stations was in the upstream reaches at 3.73 m³/s and 2.36 m³/s at the confluences. The highest concentrations of heavy metals in the water for the dry and wet seasons were 0.09 ± 0.01, 0.25 ± 0.01, 0.03 ± 0.02, 0.73 ± 0.04, 4.07 ± 0.08, and 3.07 ± 0.04 mg/L, respectively, for Pb, Cr, Cd, Cu, Zn, and Ni. The order of magnitude of the heavy metal concentration in the sediments was Zn > Ni > Cr > Cu > Cd > Pb, while the highest NO₂⁻, NO₃⁻_, NH₃, and PO₄³⁻ in the water and sediment were 2.05 ± 0.01, 0.394 ± 0.527 0.66 ± 0.05, and 0.63 ± 0.01 mg/L, and 2.64 ± 0.03, 0.63 ± 0.01, 2.36 ± 0.01, and 48.16 ± 0.01 mg/kg, respectively, across all sampling seasons. This study highlights the significant impact of urbanization on river integrity, revealing elevated levels of heavy metal contamination in both water and sediment, the variability of discharge, and alterations in the LULC in the rivers’ buffer. This study recommends the continuous monitoring of the river water quality and quantity of the urban rivers, and the overall land-use plans for conserving river ecosystems. Full article

In recent decades, a plethora of natural disasters, including floods, storms, heat waves, droughts, and various other weather-related events, have brought destruction worldwide. In particular, Algeria is facing several natural hydrometeorological and geological hazards. In this study, meteorological parameters (precipitation, temperature, relative humidity, wind speed, and sunshine) and runoff data were analyzed for the Wadi Ouahrane basin (northern Algeria), into which drains much of the surrounding agricultural land and is susceptible to floods. In particular, a trend analysis was performed using the Mann–Kendall (MK) test, the Sen’s slope estimator, and the Innovative Trend Analysis (ITA) method to detect possible trends in the time series over the period 1972/73–2017/2018. The results revealed significant trends in several hydro-meteorological variables. In particular, neither annual nor monthly precipitation showed a clear tendency, thus failing to indicate potential changes in the rainfall patterns. Temperature evidenced a warming trend, indicating a potential shift in the local climate, while streamflow revealed a decreasing trend, reflecting the complex interaction between precipitation and other hydrological factors. Full article

The controlling hydrogeochemical processes of an intermontane aquifer in central Mexico were identified through multivariate statistical analysis. Hierarchical cluster (HCA) and k-means clustering analyses were applied to Na⁺, K⁺, Ca²⁺, Mg²⁺, F⁻, Cl⁻, SO₄²⁻, NO₃⁻, HCO₃⁻, As, pH and electrical conductivity in 40 groundwater samples collected from shallow and deep wells, where As and F⁻ are contaminants of concern. The effectiveness of each hierarchical and k-means clustering method in explaining solute concentrations within the aquifer and the co-occurrence of arsenic and fluoride was tested by comparing two datasets containing samples from 40 and 36 wells, the former including ionic balance outliers (>10%). When tested without outliers, cluster quality improved by about 5.4% for k-means and 7.3% for HCA, suggesting that HCA is more sensitive to ionic balance outliers. Both algorithms yielded similar clustering solutions in the outlier-free dataset, aligning with the k-means solution for all 40 samples, indicating that k-means was the more robust of the two methods. k-means clustering resolved fluoride and arsenic concentrations into four clusters (K1 to K4) based on variations in Na⁺, Ca²⁺, As, and F⁻. Cluster K2 was a Na-HCO₃ water type with high concentrations of As and F. Clusters K1, K3, and K4 exhibited a Ca-HCO₃, Na-Ca-HCO₃, and Ca-Na-HCO₃ water types, respectively, with decreasing As and F concentrations following the order K2 > K3 > K1 > K4. The weathering of evaporites and silicates and Na-Ca ion exchange with clays were the main processes controlling groundwater geochemistry. The dissolution of felsic rocks present in the aquifer fill is a likely source of As and F⁻, with evaporation acting as an important concentration factor. Full article

In recent years, accessing rainfall data from ground observation networks maintained by national meteorological services in West Africa has become increasingly challenging. This is primarily due to high acquisition costs and the often sparse distribution of rainfall gauges across the region, which limits their use in hydrological studies and related research. At the same time, the rising availability of precipitation products derived from satellite/earth observations, reanalysis datasets, and in situ measurements presents exciting prospects for hydrological applications. Nonetheless, these datasets constitute indirect measurements, necessitating rigorous validation against ground-based rainfall data. This study comprehensively assesses twenty-three gridded rainfall products, including sixteen from satellites, six from reanalysis data, and one from in situ measurements, across the Senegal, Gambia, and Casamance River basins. Performance evaluation is conducted across distinct climatic zones, both pre- and post-resampling against observed rainfall data gathered from forty-nine rainfall stations over a six-year period (2003–2008). Evaluation criteria include the Kling–Gupta Efficiency (KGE) and Percentage of Bias (PBIAS) metrics, assessed at daily, monthly, and seasonal time steps. The results reveal distinct performance levels among the evaluated rainfall products. RFE, ARC2, and CPC notably yield the highest KGE scores at the daily time step, while GPCP, CHIRP, CHIRPS, RFE, MSWEP, ARC2, CPC, TAMSAT, and CMORPHCRT demonstrate superior performance at the monthly time step. During the rainy season, these products generally exhibit robustness. However, rainfall estimates derived from reanalysis datasets (ERA5, EWEMBI, MERRA2, PGF, WFDEICRU, and WFDEIGPCC) perform poorly in the studied basins. Based on the PBIAS metric, most products tend to underestimate precipitation values, while only PERSIANN and PERSIANNCCS lead to significant overestimations. Spatially, optimal performance of the products is observed in the Casamance basin and the Sudanian and Sahelian climatic zones within the Gambia and Senegal basins. Conversely, in the Guinean zone of the Gambia and Senegal Rivers, the rainfall products displayed the poorest performance. Full article

A natural wetland receiving drainage from a 24-ha urbanized catchment in the Falls Lake Watershed of North Carolina was evaluated to determine if it was providing ecosystem services with regards to phosphate and Escherichia coli (E. coli) attenuation. Inflow and outflow characteristics including nutrient and bacteria concentrations along with physicochemical properties (discharge, pH, oxidation reduction potential, temperature, and specific conductance) were assessed approximately monthly for over 2 years. The median exports of phosphate (0.03 mg/s) and E. coli (5807 MPN/s) leaving the wetland were 85% and 57% lower, respectively, relative to inflow loadings, and the differences were statistically significant (p < 0.05). Hydraulic head readings from three piezometers installed at different depths revealed the wetland was a recharge area. Phosphate and E. coli concentrations were significantly greater in the shallowest piezometer relative to the deepest one, suggesting treatment occurred during infiltration. However, severe erosion of the outlets is threatening the stability of the wetland. Upstream drainageway modifications were implemented to slow runoff, and septic system repairs and maintenance activities were implemented to improve water quality reaching the wetland and Lick Creek. However, more work will be needed to conserve the ecosystem services provided by the wetland. Full article

This study investigates the dynamics of water resources in the Citarum watershed during periods of weak La Niña, normal, and weak El Niño conditions occurring sequentially. The Citarum watershed serves various purposes, being utilized not only by seven (7) districts and two (2) cities in West Java, Indonesia but also as a source of raw water for drinking in the City of Jakarta. Using a time-series analysis of surface water data, data-driven (machine learning) methods, and statistical analysis methods, spatiotemporal predictions of surface water have been made. The surface water time series data (2017–2021), obtained from in situ instruments, are used to assess water resources, predict groundwater recharge, and analyze seasonal patterns. The results indicate that surface water follows a seasonal pattern, particularly during the monsoon season, corresponding to the groundwater recharge pattern. In upstream areas, water resources exhibit an increasing trend during both weak La Nina and weak El Niño, except for Jatiluhur Dam, where a decline is observed in both seasons. Machine learning predictions suggest that water levels and groundwater recharge tend to decrease in both upstream and downstream areas. Full article