Recent Advancements from Aquifers to Skies in Hydrogeology, Geoecology, and Atmospheric Sciences

Groundwater being the most abundant source of freshwater for the survival of flora and fauna is expected to meet the demands of agriculture, industry, and drinking water requirements. Due to climatic changes and over-exploitation, the total groundwater reserve has decreased. The only way out of this quagmire is to use the resource judiciously and recharge frequently. Not all regions are suitable for recharge due to differences in hydrological settings. As a result, determining the ability of an area to retain water is pertinent. This study proposes a demarcation of groundwater potential zones using eigenvectors on a grid within the Periyar River Basin (PRB) in Kerala, India. The PRB is Kerala’s second largest river basin, serving the domestic, agricultural, and industrial needs of the metropolitan Kochi. Over PRB, the grid of approximately 11.1 km-by-11.1 km in length and points within 1.11 km of each other is considered. The variables used for the analysis are Normalized Difference Vegetation Index, Soil Moisture, Lineament Density, Sand content, Silt content, Clay content, Drainage Density, Slope, Rainfall and Temperature. The eigenvectors are computed for the matrix deformed using the grid point variable values. Satty’s Scale and Analytical Hierarchical Process are used to calculate the weights. The basic method employs several weighting approaches to the layer subclasses, which increases the uncertainty in the final output. This volatility has been morphed using the developed method. On a seasonal scale, the dominant eigenvector that explains the most variability is used to form the groundwater potential zones (GWPZ), namely low, moderate and high during the months of January, April, August and November of 2020. Validation is based on actual groundwater levels (GWL) in the 9 observation wells managed by the Central Groundwater Board (CGWB). Based on the results, seven wells in January and six in November reached the expected potential zone class, while one of the wells encountered over-exploitation at the considered PRB grid point. Overall, the agreement between the groundwater levels and the potential zone delineation is 72.2%. This developed method can be applied in different locations to delineate GWPZs. An accurate potential map aids in source monitoring, assessment and protection.

The Moroccan septentrional region includes the Bassin du Saïss. Due to this bassin's enormous surface area and substantial depth, our current understanding of it is still limited and fragmentary. To improve understanding of the aquifer, a 3D geological model was developed using data from over two hundred boreholes, eight geological maps, and a digital terrain model. The data was processed using a Geographic Information System (GIS) and a geological modeling software, with consideration given to five lithostratigraphic units: Paleozoic, Triassic, Jurassic, Miocene, and Plio-Quaternary. The developed model provides a precise visualization of the geometry and stratigraphy of the basin, as well as a better understanding of the deep Lias aquifer and its hydrogeology. The study results provide a valuable conceptual model that can be used to reinterpret existing geophysical data and assess the extent of the Lias aquifer. Furthermore, the results can contribute to the development of a hydrogeological model that simulates the hydrodynamic functioning of the aquifer under variable climate and exploitation conditions.

Salt springs in Cambrils del Pirineu (Pyrenees, NE Iberian Peninsula) are related to diapirism of Triassic (Keuper) evaporite-bearing deposits. Such brines, which are close to NaCl saturation, have been used at least since s. XVIII to produce non-marine table salts. The present research aims to study the hydrogeological system in a high salinity spring water from mountain source in the southern Pyrenees using geochemical study of water and its association with local geology. The research includes total conductivity, major anion and element analyses by means of HPLC and ICP-OES and water flow measurements for one-year period. Sampled waters include a salty spring and nine closer freshwater springs. Conductivity of the salt water is close to 44 mS/cm, chloride is about 17% and Na is close to 10%, with minor amounts of sulphate, K, Ca, Mg and Sr. Water flow is about 4 L/min (July 2021 to June 2022). Minor increase in the flow rate is related to superficial inflows during last metres of brine circulations before outcropping. Freshwater springs have HCO3-Ca compositions but show a slight Mg-SO4 enrichment due to nearby Triassic evaporites. Eh of brine at source is only of 12 mV, thus evidencing its reductive behaviour. Local geology suggests large brine circulation along Triassic-Cretaceous contact until surface discharge. This model differs from previous interpretations, which pointed to more superficial recharge and fluid circulation.

This research aims to investigate the influence of climate change on the groundwater level (GWL) in Mornag plain in Tunisia. Due to the spatiotemporal variability of rainfall (RF) and temperature, aquifers all over the world have seen significant water level decline in recent decades. Therefore, it is crucial to analyze and estimate the GWL variability for reliable groundwater (GW) management in the context of climate change. In this study, we focus on the plain of Mornag, located in the southeast of Tunisia, since it contributes 33% of the national agricultural production. From this plain, we have collected historical piezometric and RF data covering the period 2005–2015. Knowing the RF data, our goal is to forecast the GWL. This issue has already been investigated using numerical GW modeling tools such as Modflow and Feflow. Unfortunately, these techniques are data and time-consuming. To overcome all these drawbacks, we propose to use an Artificial Intelligence (AI) approach that has shown great performance in the literature for recurrent data modeling and forecasting. This approach corresponds to the Long Short-Term Memory (LSTM) Neural Network. Compared to Modflow, LSTM showed a notable improvement in terms of minimizing the mean square error, confirming its suitability for GWL forecasts. Using the proposed AI prediction model, the impact of climate change on Mornag GWL has been studied under two Representative Concentration Pathway (RCP) scenarios; RCP 4.5 and RCP 8.5 for three future periods: 2015–2040 (short term), 2041–2065 (medium term), and 2066–2100 (long term). As expected, the results reveal a future decline for Mornag GWL. The performed study of future Mornag GWL behavior using LSTM could classify this AI approach as a good decision support system that could be used to optimize the management of our limited water resources to satisfy the population needs for drinking water and agricultural production, as well as to avert upcoming drought.

The aim of this study is to assess, within a GIS, the pollution risk of the Mornag groundwater using the DRASTI-LU and SI index methods, and to validate the resulting maps with geochemical data. To achieve this objective, four risk maps were created by combining hydrogeological and geochemical data. 41 samples were analyzed to validate the risk maps developed. Each risk map was calcified using four reclassification methods so that a total of 16 risk maps were produced. The spatial distribution of groundwater contamination risk allowed results to be compared by classifying them into five risk classes: very low, low, medium, high, and very high. All the resulting risk maps show that the downstream part of the aquifer is the riskiest to pollution compared to the other areas. In fact, the results of validation of the risk maps show that relatively the best map with the lowest correlation index is the one made by the DRASTI-LU method obtained by the additive combination with a weight of 5 for the land use parameter. The coincidence between the nitrate concentration distribution and the spatial distribution of risk degree confirms that the study area is affected by anthropogenic pollution more precisely agricultural pollution by nitrates.

The Haouz aquifer faces multiple environmental and socioeconomic challenges largely related to climatic aridity and to the growth of the agriculture sector. By combining several methods such as cascade analysis, cross-correlation and Principal Component Analysis (PCA), this study conducts a comprehensive analysis of hydroclimatic data in order to comprehend the interactions between water management components. The findings indicate that there are three different groundwater functioning systems. The first system is noticeable in areas with extensive irrigation from groundwater. The water cycle’s natural balance is disturbed, and surface water's contribution to groundwater recharge is negligible. The second and the third systems are manifested in areas where pumping is low. The hydrological cycle balance is preserved, which exhibits a cascading effect in all of its studied elements and a noticeable contribution from surface water to groundwater recharge. To promote effective groundwater management, this study has made data and graphics available to reveal the challenges related to groundwater vulnerability to climatic aridity and overexploitation in the Haouz region.

CO2 geological storage has been investigated and carried out as a strategic approach to mitigate climate change caused by drastic increase of CO2 emission to the atmosphere in the past 20 years. To offset the cost associated with sequestration, partial stored CO2 can be circulated to harvest geothermal energy from the deep reservoir, which has been demonstrated more efficient than conventional water-based method. This study aims to model CO2 sequestration and subsequent geothermal production in a heterogeneous reservoir in North Oman. CO2 injected, net storage, spatiotemporal distribution of reservoir pressure, temperature and CO2 plume, and recovered geothermal energy are assessed based on the model simulation. The findings provide a preliminary feasibility evaluation of operating CO2 sequestration and CO2-circulated geothermal recovery in similar reservoirs in North Oman and worldwide.

In the region of Regueb, central Tunisia, agriculture represents the first socio-economic activity and has experienced a considerable extension of irrigated areas which has been accompanied by intensive exploitation of deep waters. The management of these resources is becoming increasingly difficult, and hydrogeological studies of groundwater resources are furthermore required. The multi-layered aquifer system of Regueb is yielded in sandy and sandy-clay formations intercalated by impermeable to semi-permeable Mio-Plio-Quaternary levels. It includes a superficial aquifer level exploited by surface wells and a semi-deep to deep level drilled by deep wells, especially in the south-eastern and north-eastern parts of the basin. The examination of the piezometric data from available wells allowed us to distinguish two areas with different piezometries apparently separated by an E–W edge. The northern area is restricted to the north of Regueb city and exhibits an outflow towards Sebkha Mchiguig, and the southern one is relatively wide and extends overall the basin between Regueb and Mezzouna cities. The groundwater salinity ranges between 2 and 8.5 g/L and increases to the north of the basin, however, nitrates concentrations are relatively increased in the eastern part of the basin in correlation with agricultural activity.

The Tadla plain located in the Oum Er-Rbia River Basin constitutes one of the principal agricultural production areas in Morocco. The groundwater resources are derived from the karst aquifer of the Atlas Mountains and the multilayered system (superficial and deep aquifers) of the Tadla plain. The Turonian constitutes the main productive aquifer in the area. The isotopic composition and concentration of strontium in 43 groundwater samples, combined with solute concentration data, provide important details regarding groundwater geochemical evolution, flow pathways and mixing processes in the Tadla multilayered aquifers. Shallow aquifers are characterized by significantly higher salinity, particularly in irrigated perimeter areas (Beni Amir and Beni Moussa). The relationship between chloride and EC shows a similar correlation for all water groups, except for some Atlas springs with conspicuously lower chloride/EC ratios. Stable isotopes suggest that the waters originated from meteoric water that was infiltrated into the different aquifers through permeable formations without secondary surface evaporation. The strontium isotope ratios of low saline water from the Turonian aquifer and the High Atlas spring waters overlap and show mixing (0.7078–0.7092) between Sr derived from the Turonian age limestone aquifer (0.703) and a higher 87Sr/86Sr source. Two types of chloride saline water were found in all aquifers: (i) low 87Sr/86Sr (0.7078) and Br/Cl (1.7 × 10–4) source that affects groundwater in the Turonian and Senonian aquifers. This type of water is originated from the dissolution of gypsum and halite deposits. (ii) High 87Sr/86Sr (0.7110) and marine Br/Cl (~ 1.5 × 10–3) source that occurs mostly in the Eocene aquifer.

In the last decades, scientific attention has grown toward vulnerability assessment of drinking water quality. Groundwater is a crucial resource for drinking water needs, and its vulnerability to contaminations is associated with natural and anthropic processes. The vulnerability of wells tapping confined aquifers is frequently associated with natural contamination by reduced species (e.g., As), while anthropic contamination is considered less relevant. Nevertheless, mixing processes induced by water pumping and related to the well structure can determine the presence of a shallower water fraction in the extracted water, which increases wells vulnerability to anthropic contamination. In this study, redox zonation is applied to water quality data of 16 drinking water wells tapping confined aquifers to assess the main processes affecting water quality. All the considered wells resulted under reducing conditions at different redox states. Three wells showed evidence of mixing processes between shallower and deeper waters. In these cases, mixing processes lower the concentration of As, but increase the vulnerability toward anthropic contamination.

The ongoing energetic transition needs critical raw materials such as lithium or other metals and renewable energies, such as low to mid-enthalpy geothermal energy. Geothermal systems, mostly located near plate boundaries, undergo strong structural controls essentially through crustal faults, also known to drain fluids. Furthermore, dissolved metals in geothermal fluids can be exploited as a byproduct in geothermal plants. In the present, study we define spatial variations in metal content and the structural control along the Vallès Fault, as a field analogue of a passive margin domain. The Vallès Fault is a crustal fault that juxtaposes the Miocene detrital basin infill to a syn- and late-Hercynian granitic basement. With a crustal thermal anomaly, a geothermal gradient > 35 °C/km, several geothermal systems of low enthalpy (< 130 °C at 1 km depth) are closely associated to the Fault. These geothermal systems are revealed by several springs with temperatures ranging from 20 to 75 °C. The present work combines hydrogeochemical, structural and petrological approaches to characterize the architecture and the relative chronology of the fracture networks of the sites of hot springs; and the metal content of thermal waters to reconstruct the spatial evolution of the metal content of the geothermal fluids. From the structural and petrological point of view, three main results are highlighted: (1) the footwall of the Vallès Fault is characterized by a network of polyphase fractures affecting the granite basement and constituting an important network of permeability by fracturing; (2) a thick fault zone with cataclastic to ultracataclastic fault rocks constitutes, a priori, a barrier for fluids circulation; and (3) an arkosic Miocene basin infill, affected by secondary faults, constitutes a very good reservoir. The metal content of hot waters is low but significant to establish differences according to their structural position. Tectonic structures and surrounding lithologies seem to be decisive in water compositions.

The coastal region of Rhodope (NE Greece) is characterized by increased salinization risk leading to groundwater quality degradation and water scarcity. In the context of the MEDSAL Project ( www.medsal.net ), a comprehensive assessment has been carried out concerning the hydrogeochemical characteristics of the area while evaluating the potential impact of geothermal fluids circulation and their ability to move upward and contaminate more surficial water bodies. According to previously conducted surveys, three geothermal wells have been identified in the study area, two of which are representative of the geothermal reservoir, which is hosted within Tertiary molassic sediments. To get an insight into the current hydrogeochemical conditions, a sampling campaign was performed, during which 46 groundwater samples were collected and analyzed for a wide set of parameters. Based on the analytical results, elevated concentrations of certain trace elements presumably associated with geothermal activity (indicatively referred to as B, Li, Sr, and U) have been detected in groundwater wells close to the geothermal one, indicating a possible connection. The relatively elevated groundwater temperature, which reaches up to 25.1 °C, as well as the electrical conductivity values, additionally supports the aforementioned connection. In order to better understand the potential connection of the geothermal influence, the analytical results have been further processed using different tools. The outcomes of the spatial distribution of Li, U, and Ce denoted that the groundwater wells, which are located close to the reported tapped geothermal reservoir and the dominant tectonic structures that prevail in the area, seem to follow a similar hydrogeochemical pattern.

Salt springs in the Pyrenees (NE Iberian Peninsula) are common due to diapirism and dissolution of Triassic evaporite-bearing deposits. Various salty sources from Eastern Pyrenees have been analysed in order to elucidate their accurate chemical and isotopic composition. The study includes trace analyses by means of ICP-OES and ICP-MS, and, sulphate (S–O) and water molecule (H–O) isotope analyses by mass spectrometry. Outcropping Na–Cl rich brines contain B, Li (from 0.17 to 2.43 ppm), Rb, Zn and Mn as main trace elements. The origin of the salty composition is due to fluids circulating through evaporite Keuper facies (Triassic; halite-sulphates, calcium carbonates and clays), as clearly revealed by brine S–O isotope signature. Sulphate molecule has not suffered sulphate reduction, thus evidencing simple rock dissolution. Noticeable lithium content in seawater brines is well known due to the conservative behaviour of such element, which increases during evaporation. Studied salty springs are non-marine in origin, and not clearly related to hydrothermalism or volcanic fluids, which will enrich brines in lithium. The negative H–O and C isotope signatures of water also support this evidence. Thus, Li origin is mainly due to dissolution of Keuper evaporites, both considering Li contained in salt rocks and/or in fluid inclusions. Study of such brines will contribute to a better understanding of Li circulation and storage in non-marine salty springs.

The study is the first in the El Oued region. It was based on a descriptive statistical approach to analyze and process hydrogeochemical and bacteriological data of groundwater draining detrital and carbonate sedimentary geological formations to develop water quality classes for the aquifers in the study area and to valorize them. The study area is in northern Morocco, in the northern Rif. The latter is a part of the Flyschs aquifer and a part of the Calcareous-Dorsal of the Rif chain southeast of the Tetouan city. The principal Calcareous-Dolomitic and detrital geomorphic unit formations provide an important reservoir in the study area. Recharge of these aquifers is deeply linked to the direct precipitation. The atomic spectrometry and the titrimetric methods analyzed fifteen groundwater samples from springs, boreholes, and hand-dug wells. They were the subject of a physical–chemical (EC, temperature, pH) measurement in situ, a chemical-bacteriological analysis (Ca2+, Na+, K+, Mg2+, TAC, TDS, Cl−, HCO3−, SO42−, NO3−, fecal coliforms) in the laboratory, and a hydrochemical study. The aquifers in the study area are generally of two types: fissured aquifers and porous media aquifers. The physicochemical and bacteriological data show that the water in the aquifer system of the study area was generally clear of Nitrate and of excellent to very good quality. These results were confirmed by the Water Quality Index (WQI ≤ 41.46) and the Principal Component Analysis (PCA). Three geochemical water facies were distinguished: a calcium chloride dominated water (Numidian Flysch), a calcium bicarbonate dominated water and a calcium magnesium bicarbonate dominated water (Beni Ider Flysch, Limestone and Dolostone). Based on the Electric Conductivity (EC) and the sodium percentage (%Na) classification, 93.34% of the water samples were considered excellent and 6.66% were considered as good for irrigation purposes. While, based on the EC and the SAR classification, 26.7% and 73.3% of groundwater samples indicate excellent and a good to somewhat good water quality, respectively.

The Rhodope coastal area (NE Greece) is an intensively cultivated agricultural region with profound signatures of water quality deterioration because of elevated salinity. Within the MEDSAL Project ( www.medsal.eu ) activities, a thorough study of hydrogeochemical characteristics was performed to assess the extent of groundwater salinization and identify its dynamics. A combined suite of hydrogeochemical tools was applied to the data of forty-six (46) groundwater samples collected in June 2020. Calculating salinization facies (SFs) allowed classifying samples according to their chloride content. The salinization phenomenon is evident since nearly 30% of groundwater samples result in brackish (B) or brackish saline (Bs) with Cl− > 1000 mg/L). Most saline samples (B and Bs) are distributed in two areas close to the coastline. Nevertheless, seawater intrusion is not the dominant salinization cause, as the effect from an additional diluted brine is profound. The fresh (F) and fresh-brackish (Fb) waters are located further inland than the B sample. However, they do not show any definite spatial pattern distribution. Considering the hydrogeological regime of the area, the F samples are likely to be significantly affected by the deeper (confined) aquifer layer of better qualitative conditions. Based on a series of binary plots of major elements versus Cl−, we conclude that salinization may result from one single source or a combination of more sources from place to place. According to previous reports and surveys, additional cascading sources may include trapped saline lenses and irrigation water return.

Located on the Moroccan Atlantic coast, coastal Chaouia aquifer, the region’s subject of this study, constitutes the most extensive aquifer. It is composed mainly by a complex aquifer of geological formations from Ordovician-Cambrian, Cretaceous and Pliocene–Quaternary age, respectively. The geostatistical method by kriging, applied to piezometric data of 2009 and 2011, draws the evolution of water levels in these periods. The comparison of the obtained piezometric maps shows a seaward move of the potentiometric line 0 m, in 2011, which has been related to the importance of 2010 rainfall. The flow of water table is always oriented toward the sea with a convex trend of the piezometric curves at the vicinity of Oum Er-Rbia River, showing a permanent drainage phenomenon, proving that the piezometric level of the groundwater remains constantly above the level of the river water. Besides, piezometric chronicles recorded in the aquifer formations indicate that the piezometry of the water table is mainly related to possible changes in recharge rate under the rain.

Water availability in arid basins is a serious concern and its quantification remains uncertain. Climate variability as the El Niño Southern Oscillation phenomenon (ENSO) can worsen this scenario, exacerbating flooding in some regions such as the Piura basin on the northern Peruvian Pacific coast. We analyzed four geospatial runoff datasets covering a 7622 km2 basin area at ~50 km of resolution. They are two global datasets: Global Runoff (GRUN) and Linear Optimal Runoff Aggregate (LORA) based on both hydrological reanalysis; a Peruvian dataset named PISCO-Hym-GR2M based on satellite and in-situ conceptual water balance; and a semi empirical method called Rindex based only on in-situ conceptual water balance. Those monthly datasets were compared to historical observations over four selected ENSO events which accelerated and retarded the peak monthly runoff and reached up to 317 mm/month. GRUN, LORA, PISCO-Hym-GR2M and Rindex reached month predictions of 42%, 21%, 58% and 50%, respectively with an acceptable relative error below 50% during the December–May wet period. Using hydroclimatic match indices in a Taylor diagram, correlations coefficients over 0.75 were obtained for all products, the highest corresponding to the GRUN dataset. A reliable root mean square difference near 40 mm/month for GRUN and Rindex; and a reliable amplitude of the variations for PISCO-Hym-GR2M and Rindex around 80 mm/month were obtained. Most datasets underestimated runoff with shifts in peak monthly runoff timing related to spatial aggregation of input precipitation, being LORA the most accurate in matching peaks. Those products could help to study monthly runoff fluctuations, knowing their difficulty in prediction.

In the high Atlas Mountains of Morocco, forecasting discharge is of crucial importance for water resource management but it remains a difficult task due to the scarcity of observations. This study presents meteorological re-analysis data as a promising alternative for feeding hydrological model where observation data are absent. Re-analysis data are used here as inputs to a ‘Support Vector Regression’ (SVR) algorithm to simulate the daily discharge over the Rheraya catchment in Tensift, Morocco. The SVR model is calibrated, and its accuracy is assessed using a time series from September 2003 to August 2016. The efficiency of daily predictions of streamflow is compared with the daily-observed discharge. SVR model fed by re-analysis data showed a good performance during the test period with an NSE and RMSE respectively equal to (0.88 and 0.89 m3/s). This accuracy is mainly due to the high correlation between the discharge and the predictors. The SVR model fed by re-analysis data can be considered as a reliable tool to estimate daily discharge.

Flash floods are among the deadliest natural hazards. With the increase of worldwide population, many more lives could be at risk. Hydrological modeling methods have significantly evolved in the last years. Also, new methods have emerged like machine learning. However, it is still challenging to anticipate and plan crisis management actions like evacuation. Crisis managers and hydrologists often work individually. Hydrologists will often forecast hydrological variables like discharge. Nevertheless, apart from big cities, crisis management plans are rarely based on this variable. The forecasts are, therefore, unlikely to be used regardless of their informational value. Thus, this study aims to identify relevant information for crisis management using different configurations of forecast bulletins. The study site is the flash-flood prone watershed of Gardon d’Anduze (545 km2) in Anduze, Southern France. Floods can cause the discharge to increase from 100 l/s to 3000 m3/s in about ten hours. Using artificial neural networks, water level and discharge were forecasted. From these forecasts, six different bulletins were proposed with variant types and levels of information like future rain, discharge at upstream watersheds, and threshold markers. To evaluate their relevancy, records of decisions, observation sheets, discussions, and surveys were used. The bulletins were then tested in a crisis management simulation setting with operational managers. The main findings are as follows: (1) the usefulness of reference to previous events depended on each crisis manager’s personal experience, (2) discharge was difficult to interpret, (3) confidence in forecast bulletins was medium to high, (4) crisis managers were generally able to make decisions with satisfying degrees of anticipation regardless of the level of information, (5) they also preferred bulletins with the highest level of information due to an increase in visibility. This work showcased the importance of flash-flood forecast bulletins in crisis management and the reliability of neural networks forecasts.

Our study consists of analyzing the hydrological behavior of the Congo River to detect the anomalies observed which have negatively impacted navigation for several years. The databases of the Research Institute for Development (RID) and the Excel files of the Joint Waterway Maintenance Service (JWMS) were used, namely (IL Consulting Engineers in Study for the dredging of Brazzaville-Hydraulic study report. FED, 2006) for different parameters: (i) daily water heights from 1972 to 2006; (ii) monthly discharges from 1902 to 2005; (iii) water levels from 1953 to 1995; (iv) gauging results from 1982 to 1994. These results reflect the degradation of the hydrological behavior of this arm of the Congolese river on the right bank, with negative consequences on navigation. The negative consequences of this phenomenon require preventive dredging. In addition, studies should be carried out to help promote a significant inflow of water in the main channel which runs alongside the port of Brazzaville during low flow.

The expansion of intensive irrigation in the central part of Tunisia has introduced the challenge of groundwater sustainability as water table is lowering at the rate of 1–2 m per year. More productive and resilient agriculture requires changes in natural resources management, particularly water and energy. Smart water management for precision irrigation in agriculture is essential for enhancing crop yield and efficient use of water, improving irrigation scheduling, decreasing farming costs while sustaining the environment. It also contributes to make agriculture more resilient to future water-related shocks and global economic changes. Within Sustainable Production in Water Limited Areas of Mediterranean Agro-Systems (SUPROMED) project, we have selected two groups of farms situated in the same areas with similar environmental conditions. In the first sample, the irrigation of selected crops (wheat, oat, olive, pistachios and almond trees) was scheduled by MOPECO model according to soil characteristics, crop types, weather conditions and irrigation network characteristics. For the second, the farmers were left to perform the prevailing water irrigation management. The main objective of this study was to assess the MOPECO irrigation scheduling at the farm level. Agronomic yields, water productivity, farmer’s income and gross margin resilience towards market prices variability were used as indicators to compare such management to the prevailing one. Results showed that smart irrigation management allowed better yields and water use productivity, comparative to conventional management. The farmer’s incomes were also higher. Results also showed that under smart management the gross margin of selected crops become more resilient towards market prices variability leading thus to better economic viability of farming systems in the water limited environments.

This study investigated the impact of land use change on mean annual discharge in an experimental sub-basin in the metropolitan area of Athens, Greece, using the Soil and Water Assessment Tool (SWAT) model. The study site, the NW sub-basin of the Kifisos river basin, experienced an increase in artificial surfaces from 42.1 km2 in 1990 to 71.6 km2 in 2018. Therefore, the selected study site is an excellent case study to quantify the impact of urbanization on water balance components. The simulated discharge was compared to four land use scenarios (i.e. land use maps: 1990, 2000, 2006, and 2012) under the same climate conditions. Results showed that from 1990 to 2018: (i) the expansion of urban areas led to an increase of discharge by 8.7%, as water yield increased and evapotranspiration decreased, (ii) under the same climate conditions, runoff changes were observed during the late dry season, and (iii) the impact of land use change was more noticeable in the suburban sub-basins with significant urbanization. Overall, the outcomes of this study provide essential knowledge of the hydrological processes of an urban/peri-urban system which will be useful for planning future development strategies in the region.

The Souss basin in Morocco is distinguished by an uneven surface water supply and steady overexploitation of groundwater resources. In recent years, the basin experienced constant disrupted water balance, due mostly to year-to-year variable weather conditions and rising water demand. This situation is projected to affect the region’s economic development and threaten the prospects of many economic sectors. Therefore, this study was conducted to analyze the water balance of the Souss basin as well as to develop a decision support tool (DSS) to assist water sector managers in sustainable water governance. MODSIM 8.1, a generic river basin management decision support system, for water allocation modeling designed as a computer-aided tool, was selected for that study. Once calibrated and validated over the period from 1990 to 2019 using recorded data about physical processes and hydraulic infrastructures, the model is used to simulate water supply and demand in the Souss basin. The findings indicate that the basin’s water resources are vulnerable, and dams’ inputs in the basin have undergone significant fluctuation under both changing climate and increasing water demand in the growing area. In addition, there is a significant amount of unmet demand across all demand sites. As result, the average total unmet demand for surface water from reservoirs in irrigated areas reached 201 mm3 between 1990 and 2019, and the monthly average demand increased by 55% in the dry season, compared to the demands in the rest of the year. The significant amount of unmet demand across all demand sites suggests that demands are satisfied by the withdrawal of water from groundwater resources. Using MODSIM, the adopted simulation approach has shown to be a useful decision support tool to understand water resources planning challenges. Water managers require reliable tools to represent the basin’s various trade-offs with regards to water resources. Thus, an investigation improving the representation of groundwater/surface water interaction in operations modeling is required to enhance the evaluation of the consequences of different uses at the basin level.

The “lower Chaouia” or coastal Chaouia region, which is the most agricultural part of the coastal Chaouia, is a sub-Atlantic plain that has developed along the Atlantic Ocean. To ensure the integration of sustainable aquaculture in this region, a study was conducted to identify the specific richness of the environment. It consisted of the mapping of physicochemical parameters and a sedimentary study for the exploration of potential algaculture sites. To conduct this study, a database was built from a combination of satellite data. Besides, field measurements were also carried out during the oceanographic investigation missions of the study area to understand the temporal variability of the various parameters with the help of geographic information system (GIS) tools. The treatment and analysis of all the data collected revealed important macroalgal biodiversity in the Sidi Rahal Chatai area. Indeed, in this relatively rich environment, where the maritime zone (located between the coastline and the rocky strip offshore) which remains covered with seawater, with a depth of water greater than 30 cm, is home to more than 22 species of marine macroalgae. The particle size study of the sediments shows that the bottom consists of the rocky sand type which promotes the fixation of algae. The actual variability of some environmental parameters confirmed the suitability of this area for algae cultivation. For this reason, algaculture is an alternative solution for preserving algae. It is an environmentally friendly activity that can even limit the effects of chemical and organic pollution at the local level and mitigate the effects of climate change a socio-economic activity for the development of the region.

The bottom soils of fish ponds not only influence the availability of different nutrient elements to benefit the primary food organisms but also control many important bio-geo-chemical reactions in the pond environment exerting significant influence on the pond health and, in turn, the fish growth. However, little attention is generally paid to various productivity attributing soil properties while undertaking any aquaculture operation in various soil zones. We assessed the relative effects of different soil factors on productivity of the fish ponds situated under two contrast agro-ecological regions of West Bengal, India, viz. hot-dry sub-humid (HDSH) region represented by red and lateritic soils and hot-moist sub-humid (HMSH) region exemplified by alluvial soils with the primary objectives of identifying the productivity limiting soil properties of the fish ponds of these two regions and understanding their impacts on productivity. For this, the magnitude of primary fish food production in 85 and 110 no of ponds in HMSH and HDSH regions, under culture of composite fish species, were studied in the form of net primary productivity (NPP) and correlated with relevant properties of those pond soils. NPP values were considerably lower in the fish ponds under HDSH region as compared to those under HMSH region. Statistical correlation and multiple regression analyses showed pH and available N and P status to be the key soil factors to influence the NPP of pond water in case of hot-moist region. For the hot-dry region, pH, organic C, available N and P, and clay content emerged as the major factors influencing the productivity. Among all these properties, available P was observed to be the most important soil factor influencing the net primary productivity of pond water in both the agro-ecological regions and was followed by soil pH and available N. Together, these three soil properties could explain 83 and 72% of variability in primary productivity of the fish ponds under hot-moist and hot-dry regions, respectively. The results suggest that the aquaculture practices in these two agro-ecological regions need specific management of these three soil properties for attaining better fish production.

For a decade, the preservation of water resources has become a major environmental concern in Morocco, through the National Sanitation Program which aims to collect and treat wastewater efficiently by using valuable wastewater treatment plants (WWTP) for the reuse of cleaned wastewater in agricultural irrigation, urban watering, and recovery of rivers. The acute drought that has hit Morocco and the Mediterranean basin in the last five decades has pushed the Moroccan government to issue a new law on water saving and the reuse of purified water: law 10–95. To be reused, the treated water must comply with the standards imposed by the law 10–95 and the WHO. The Casablanca region with 4 million inhabitants evacuates more than 350,000 m3 of wastewater into the sanitary network. Only 100,000 pass through wastewater treatment plants installed in the peri-urban area. The cities of Casablanca and Mohammedia use an outlet that discharges 250,000 m3 into the Atlantic Ocean without extensive treatment. The cities of Mediouna and the airport area have wastewater treatment plants based on membrane reactor technologies, and activated sludge, respectively, generate purified water with different purification yields. In this context, we studied the conformity of cleaned water in wastewater treatment plants in the peri-urban environment of Casablanca using the WHO and FAO standards for irrigation waters by analyzing different physicochemical and bacteriological parameters. Our partnership with ‘Lyonnaise des Eaux of Casablanca’ allowed us to take regular samples from two main WWTPs, surrounding Casablanca City (Mediouna and Nouaceur airport zone) and make a quality monitoring and comparative study of treatment degree of the two WWTPs. The follow-up interests: Temperature, pH, electrical conductivity (EC), chemical oxygen demand (COD), biochemical oxygen demand (BOD5), NH4+, NO3−, NKT, PO43−, and fecal coliforms. The physicochemical and bacteriological analyses of samples taken during the second half of the year 2021 showed that at the level of the station of Mediouna the registered abatement rate reached 90.9% for COD, 99.25% for BOD5, 99.1% for total suspended solids (TSS), 95.59% for Total Kjeldahl Nitrogen, and 80.20% for orthophosphate. For the airport zone, the registered abatement rate reached 90.2% for COD, 98.41% for BOD5, 99.02% for TSS, 80.07% for orthophosphate, and 83% for Total Kjeldahl Nitrogen. At the same time, the level of physicochemical quality (pH and EC) and hygienic quality for the two WWTPs are found to comply with WHO and the FAO intended for watering and irrigation.

Chemical contaminants have become a concern in terms of food security, as they immediately affect the quality of food (food safety) and can affect the availability and nutritional access to that resource (food security) over a long period. For this reason, the objective of this research work is to analyze perchlorate in aquatic food, an anthropogenic contaminant could affect human health. Samples were analyzed using micro-Raman spectroscopy. Analyzes of mussel samples collected in the Goro lagoon show the presence of perchlorate, but fortunately in very short concentration.

Qatar is one of the most fertilizer-dependent countries due to challenging soil and climatic conditions. The country strives toward self-sufficiency in agricultural production in alignment with the Qatar National Vision 2030. Hence, this work investigates the potential of utilizing nutrient-rich resources that are currently wasted for the reclamation of degraded arid soils to support the cultivation of industrial crops such as cotton (Gossypium spp.). Two abundant organic wastes, industrial biosludge and cow dung compost, were employed as soil amendments at a 3% application rate on a silty loam soil with relatively high salinity (electrical conductivity = 5.60 dS/m) and compared with conventional chemical fertilization. Cotton (May 344 variety) was then grown on the biowaste-amended soils in lysimeters for ten months (March through January) spanning through the hot season in Qatar, with the average temperature ranging from 19 to 37 °C. Soil properties and plant growth characteristics, including soil metal concentrations, days to germination and flowering, plant height, and cotton yield, were determined at set periods. The results indicated that different from the chemical fertilizer treatment, the organic amendments led to a significant release of potassium eight months after planting, roughly twice the concentration available at the initial sampling period. In all treatments, soil magnesium and iron concentrations generally increased, while phosphorus and zinc decreased over time. There was generally no significant difference in the concentrations of metals analyzed such as chromium, copper, nickel, and zinc between soils amended with the organic wastes and chemical fertilizer. The concentrations of metals were below the regulatory limits for sewage sludge applied to soils. The days to germination were 2, 9, and 11, while the days to flowering were 61, 92, and 77 for the cow dung compost, biosludge, and fertilizer treatments, respectively. The average cumulative plant heights were 74, 65, and 63 cm, while the average cumulative cotton boll yield was 7.3, 5.4, and 2.6 tons/ha, respectively, in the cow dung compost, biosludge, and fertilizer treatments. The results demonstrate that the organic amendments, especially cow dung compost, can help reclamation of degraded/saline arid soils under the described pedo-climatic conditions.

Biochar (BC) addition to soil has received a growing interest worldwide due to its numerous agricultural and environmental benefits, including nutrient retention in soil and reduction of greenhouse gas emissions. The aim of this study was to evaluate the impact of date palm residue (DPR) and its BC on greenhouse gases (CO2 and N2O) emissions and NO3-N leaching following the addition of urea fertilizer to a desert soil. The BC was produced at four temperatures: 300, 400, 500 and 600 °C (BC300, BC400, BC500 and BC600) and mixed with the soil, followed by urea addition and incubated for 40 days. The CO2 and N2O were measured periodically on day 1, 3, 6, 10, 15, 20, 25, 30, 35 and 40, whereas NO3-N in leachate was measured weekly up to five weeks. Cumulative CO2 emissions were the greatest in DPR followed by BC300 treatment, whereas the BC600 treatment exhibited the lowest CO2 emissions. The urea alone treatment showed the highest N2O emission, but this was significantly reduced with any other treatment, with the BC300 treatment providing the most pronounced effect on N2O reduction. The DPR followed by BC300 and BC400 remained the most effective treatments in reducing the amount of leached NO3-N during the whole period of incubation.

The uniqueness of the Abrau peninsula is determined by a high level of floristic and phytocoenotic diversity and the relict nature of the vegetation cover of the shiblyak—broad-leaved type of altitudinal zonality. For this mountain territory, a complex spatial organization is reviled. In this research, a cartographic method for the evaluation of the vegetation cover of a mountain territory has been approved by identifying its spatial structure. The complex analysis of field data (geobotanical descriptions) and remote sensing data (multispectral satellite images, digital elevation model) made it possible to obtain a digital cartographic model of vegetation for the key area using maximum likelihood classification with etalons and discriminant analysis. The compiled large-scale (s. 1:50,000) inventory map of the vegetation reflects the actual vegetation cover, represented by a diversity of hemixerophytic sub-Mediterranean and mesophytic nemoral communities. The change in the basic communities in the altitudinal spectrum determines the identification of two belts. The lower seaside belt of hemixerophytic forests, sparse forests, and shrub communities is expressed at heights of 0–150 (200) m a.s.l. It is characterized by the development of pistachio-juniper (Juniperus excelsa, Pistacia mutica) forests and sparse forests, oak (Quercus pubescens) forests, as well as serial vegetation with shrub and herb-dwarf shrub petrophyte-herb communities. The belt of mesophytic broad-leaved forests is located at heights of 150 (200)–450 m a.s.l. Pine-oak (Quercus petraea, Pinus kochiana) and broad-leaved (Carpinus betulus, Tilia begoniifolia, Acer campestre) forests dominate in it. The important patterns in the spatial structure of the belt are expressed within the altitudinal belts. The structure of vegetation communities is formed under the conditions of several groups of relief forms: watershed surfaces, slopes, seismic forms, erosion forms, and marine forms. The most valuable results of the investigation are connected with reviling the gradients of phytocoenotic diversity. Along with altitudinal gradient, the position on different levels of catena has significant role in its determination. The identified spatial patterns are important for understanding the formation of Northwestern Caucasus ecosystems as a part of Mediterranean region.

The objective of this study is to analyse the effect of different long-term fertilization treatments on soil microbiological and chemical properties and CO2 emissions on cropped soils. The fertilization treatments were N, P, K, NP, NK, PK, NPK, 0, which have been applied constantly for 64 years on four agricultural crops (wheat, barley, corn and beans) in rotation, in two replicates. The study was conducted on Haplic Chernozem soil type. The highest organic carbon content was observed in the treatments NPK (1.54%) and NP (1.53%), and the lowest in the control (0.97%). On average, of all measurements, CO2 emissions were largest in NP (96.28 kg ha−1 day−1), NPK (93.13 kg ha−1 day−1) and PK (79.40 kg ha−1 day−1) treatments. Strong positive correlation of mineral nitrogen with electrical conductivity, strong negative correlation with pH and moderate positive with soil organic carbon content were found. The amount of available potassium had the strongest effect on the count of actinomycetes and microbial biomass carbon. There was a positive correlation of CO2 emissions with soil organic carbon stocks and mineral nitrogen content. Long-term fertilization with NPK and NP led to enhanced accumulation of organic matter and higher available nutritious, in comparison to unfertilized soil.

The aim of the study was to assess the influence of water erosion and the applied erosion control technologies on components of soil water balance and crop productivity indicators during a three-year field experiment on Epicalcic Chernozem. Four treatments were tested: conventional technology, applied along the slope (control); conventional technology applied across the slope; surface mulching; and minimum tillage with vertical mulching with manure. The volume of surface water runoff was measured by a stationary method. The actual evapotranspiration was calculated according to the FAO 56 procedure. The water runoff was reduced in the treatments grown minimum tillage systems. On average for three years, the runoff was reduced by 435.8 m3 ha−1 for conventional technology applied across to the slope, by 524.6 m3 ha−1 for the treatment with surface mulching and by 848.2 m3 ha−1 for the minimum tillage with vertical mulching, compared to the control treatment, grown along the slope. The average grain yields for the three years range from 6026.3 kg ha−1 in the control treatment to 7018.3 kg ha−1 in the treatment with application of minimum tillage and vertical mulching. The increase in evapotranspiration in the erosion control treatments was reduced by the lower evaporation due to the plant residues on the soil surface in minimum tillage and surface mulching in the initial crop stage, despite the increased transpiration because of the lower runoffs and higher soil moisture content. This reflected in a better plant development and higher yields in maize production under these technologies.

Sub-Mediterranean landscapes with high biodiversity, rare and endemic species of flora and fauna are unique for Russia, being formed on the Black Sea coast with intensive and prolonged anthropogenic effect, in the most northeastern area of Mediterranean ecosystems of Europe. The main object of this study was the Utrish Nature Reserve, which was organized in 2010 to protect these landscapes in the North-Western Caucasus. It became a model area for large-scale complex study and monitoring of sub-Mediterranean forest landscapes under current climatic changes, including their restoration after previous anthropogenic effect. Large-scale landscape and botanical maps, compiled on the field complex descriptions on sample sites, repeated observations on the model plots with special attention to vegetation, and the analysis of remote sensing data were used to identify factors of formation, structure and dynamics of vegetation and landscapes. The relationship of vegetation to abiotic conditions was determined by statistical methods. The main factors and basic regularities of the spatial organization of vegetation and landscapes, and phytocoenotic diversity were revealed on the basis of landscape and botanical maps (1:25,000 and 1:50,000) and transects. The dominance of slope geosystems and their maximum diversity, altitudinal zonality with formation of sub-Mediterranean landscapes at 0–250 m a.s.l., the asymmetry of geosystems are typical for the landscape structure, which determines the heterogeneity of vegetation. Coastal landscapes are distinguished by the more complex spatial structure and high biodiversity with rare and relict species, including a high participation of Mediterranean species. The sea–land contact zone with the predominance of abrasion types of shores is characterized by dynamism, which leads to the destruction of part of the coastal landscapes. Vegetation restoration after recreational use and fires, including a major fire in 2020, was determined based on the study of monitoring plots. Rapid formation of herb and shrub layers began after the fire, the structure of which had both similar features in different communities and differed in its specifics. The results of the research formed the basis for expanding the boundaries of the reserve in 2021 at the expense of coastal geosystems that were not previously included and the organization of monitoring.

Mercury (Hg) is a globally distributed bioaccumulative neurodegenerative pollutant. The main way Hg enters the ecosystem is via stomatal uptake of gaseous Hg and subsequent sequestration into the soil via leaf litterfall. Thus, determining litterfall Hg concentrations will help our understanding of a key flux in Hg biogeochemistry. Concentrations of Hg in terrestrial ecosystem compartments are not well known in South-east Asia, so to rectify this deficit we determined Hg concentrations in litterfall and soil in two contrasting forest types in Terengganu, Peninsular Malaysia. We collected litterfall and soils (bulk: < 2 mm and fine: < 63 μm) from forest and heath vegetation types over coarse sandy soils and assessed Hg by an acid digestion (HCl and HNO3) and hydride generation ICP–OES technique. Litterfall Hg was 42.6 ± s.e. 2.17 ng g−1, and bulk soil Hg was 10.1 ± 2.30 ng g−1, whereas the fine soil fraction was 173 ± 20.9 ng g−1. There were correlations between Hg and macronutrient elements (C, N, P, K, Ca, Mg and S) in soil but not leaves. Total Hg return to the soil via litterfall was estimated as 16.8 μg Hg m−2 yr−1 which compares well with other global studies. Overall, our research implies that this ‘unpolluted’ location in Malaysia has Hg input comparable to other global studies, but we note that other forests in this region with greater biomass may return more Hg to the soil.

The global navigation satellite system (GNSS) provides an easy, efficient, and cost-effective way to determine position, time, and direction anywhere around the globe. However, standard GNSS can provide users with highly accurate positioning information in clear open sky environments only and often lacks consistency in maintaining required navigation performance thresholds in the urbanized environments. In such operating environments, the quality of GNSS signals is significantly degraded due to multipath (MP) and non-line-of-sight (NLOS) reception which can ultimately result in inaccurate estimation of position and navigation parameters. The MP/NLOS reception remains a potential obstacle to the practical realization of GNSS in highly urbanized environments, and the severity of the effect varies greatly with the type of environment. Thus, in order to meet stringent requirements defined for practical applications of GNSS, the characterization of signal disruption which could significantly affect a GNSS performance is highly important. In this paper, an adaptive signal quality monitoring (RSQM) method is proposed which can monitor the quality of signal and anticipate the possible degradation by investigating the temporal variations in GNSS features. The proposed RSQM method performs rigorous quality tests on GNSS fundamental features, i.e., carrier-to-noise ratio (CNR) and range residuals, and then ranks the quality of signal into three categories, i.e., best, mediocre, and worse. Leveraging the redundancy of range measurements, the RSQM selects navigation signals having the best quality and discards or de-weights the poor quality signals. To validate the performance of the proposed RSQM algorithm, a detailed study on the performance of a multi-GNSS receiver in the quad-constellation mode has been carried out on a pre-surveyed track. The experimental results show that RSQM method can accurately detect and categorize the signal quality which can help in improving the navigation accuracy by suppressing the MP/NLOS effects.

The forecasting of surface weather parameters is a key stone to every weather and climate application, and it is mainly conducted by deterministic approaches, where several uncertainty sources are faced. These limitations enhanced the reflection toward using ensemble forecasting methods, which provides helpful tools for decision-making. In this work, we aim to develop a low computational cost ensemble forecasting approach based on the analog ensemble method (AnEn), to predict six surface parameters (T2m, WS10m, WD10m, RH2m, SURFP, and MSLP) at 10 airports of Morocco for 24 forecast hours. For this goal, we use hourly observations and forecasts from the operational mesoscale numerical model AROME covering the 4-year period (2016–2019). The latter was split into training (2016–2018) and testing (2019) periods. In AnEn, the selection of analogs commonly considers only historical data for each grid point in the study domain closest to the observation site. Herein, we propose two novelties: firstly, a new weighting strategy for predictors where we use three machine learning algorithms (linear regression, XGBoost, and random forest) to assign predictors’ weights. Secondly, since AnEn requires larger training dataset to enhance chances to find best analogs, we extend the search space by integrating neighboring grid points. Thus, the analog detection is based here on 16 nearest grid points. As a result of the combination of these two techniques, it is found that the machine learning weighting strategies proved an improvement of performances in bias and root mean square error for different lead times and locations. Since the new space neighboring strategy maximizes the chances to find the best analogs, clear improvements were perceived for most airports. However, performances remain geographically dependent. In some airports, where topography is heterogeneous, applying this new analog searching strategy might lead to some worsening since weather conditions can vary at a hectometric scale.

This work reports the global ionospheric total electron content (TEC) distribution using global ionosphere maps (GIM) and Swarm satellite observations one day before and one day after the November 2021 geomagnetic storm. The November 2021 storm was the first intense storm of solar cycle 25, resulting from a cannibalistic coronal mass ejection, which is a combination of two coronal mass ejections. The main features observed were the enhancement of the equatorial ionization anomaly for up to 8 h post-storm sudden commencement (SSC), and the depletion of TEC along the equator compared to the post-storm day. Additionally, a hemispherical asymmetry was observed 8 h post-SSC in the form of an enhancement of TEC along the high-latitude northern hemisphere and depletion along the high-latitude southern hemisphere compared to the pre-storm day. This asymmetry lasted for more than 8 h. The maximum upper ionosphere (above the F2 layer peak) TEC observed by Swarm satellites started decreasing 6 h post-SSC and reached levels lower than that of pre-storm day. Additionally, the mean TEC of the upper ionosphere observed by Swarm satellites was lower for the entire post-storm day than the pre-storm day. This feature contradicts what was observed from GIM, where an enhancement of TEC was observed post-storm, particularly along low latitudes, and northern hemisphere high latitudes. This decrease of TEC in the upper ionosphere can be attributed to the lowering of the post-storm ionospheric F-region height on the dayside of the globe, as reported in previous work and confirmed empirically in this work.

Previous studies demonstrated that the El Niño–Southern Oscillation (ENSO) could modulate regional climate, thus influencing air quality in tropical latitude regions like South-east Asia. However, such influence has never been analysed in Borneo Island as it is always strongly affected by the El Niño and haze events due to the complications of the Walker and Hadley circulations that severely impact the weather in this region. To fill the gap, this study investigated aerosol concentration by aerosol optical depth (AOD) and particulate matter (PM10) in Borneo Island during the whole dynamic development of ENSO phases. The findings from this study showcased that the AOD values were usually highest in September months, mostly affecting Central Kalimantan, Indonesia, as compared to other regions in Borneo. The results suggest strong positive correlations between the aerosol optical depth (AOD) and El Niño phases, as high AOD occurred during the El Niño event. Such correlations are mainly attributed to atmospheric circulation and precipitation variation during the ENSO phase. This study further quantified the AOD variation from 2007 to 2019 attributed to changes in ENSO phases and PM10 contributions by > 50% due to anthropogenic emissions. The result also shows the importance of El Niño analysis by varying aerosol concentration (PM10) in a short-term period and a more targeted evaluation of the detected events and the specific El Niño and haze episodes.

The monitoring and prediction of the ionospheric scintillation effect which is characterized by rapid fluctuations in the phase and/or amplitude of the satellite signals is considered to be a very important aspect of space weather monitoring and remote sensing. In addition, the ionospheric scintillation poses a significant threat to satellite-based navigation services. Typically, severe scintillation can result in the occurrence of cycle slip at the tracking stage or loss of lock events which can lead to degraded navigation performance. Thus, monitoring and timely prediction of ionospheric scintillation can help in improving the accuracy and reliability of navigation services, space weather monitoring, and remote sensing. Most of the traditional methods for scintillation monitoring are based on very basic event triggers which compare the scintillation values with fixed thresholds and then identify the scintillation event. However, these conventional methods having fixed thresholds may not be effective because the occurrence and severity of ionospheric scintillation is highly dependent on the geographical location of the receiver (i.e. latitude), time of the day, and geomagnetic and solar activity. In this paper, an efficient method for accurate, timely, and automatic prediction of amplitude scintillation events is proposed. Support vector machine (SVM) is the most efficient supervised machine learning method used for classification and regression, and it classifies the data based on kernel functions. In this paper, the proposed method applies the SVM on raw global navigation satellite system (GNSS) data to detect and classify the amplitude scintillation into three main categories, i.e. no Scintillation, moderate, and severe scintillation. For this purpose, raw GNSS data were acquired by deploying a Septentrio multi-frequency GNSS receiver at Sukkur, Pakistan. The results show that the machine learning algorithms can help in developing efficient scintillation prediction models that can accurately monitor scintillation occurrence patterns and predict the scintillation events. The proposed SVM-based model achieved an accuracy of 98% which is very close to manual classification driven by human. Moreover, the prediction responsiveness is also improved, allowing early scintillation alarms.

Space debris is often perceived as a severe threat to planet Earth. These can be natural ones such as meteors and fireballs or artificial ones like rocket boosters. The UAE Meteor Monitoring Network (UAEMMN) was established to monitor space debris in the UAE sky. The UAEMMN is hosted by the Sharjah Academy for Astronomy, Space Sciences, and Technology (SAASST) and is sponsored by the UAE Space Agency (UAESA) and the University of Sharjah (UoS). The network consists of three towers distributed over three different UAE locations. The top of each tower is equipped with 17 cameras placed around a ring-like structure directed toward the sky. The system automatically captures any movement from sunset to sunrise. This paper showcases the fireballs detected by the UAEMMN system over the UAE. The UFO Analyzer and Orbit programs were utilized to define and analyze fireballs based on their apparent magnitude and visual assessment by the observer. From the date of operation of the system (September 2018) until December 2020, the network was able to classify 223 fireballs. The number of fireball detections varied over the period. However, the study reports a consistent pattern, showing that the number of fireballs tends to increase by the end of each year in November and December, coinciding with the Leonids and Geminids showers. Our UAE fireballs observations help the International Meteor Organization build a worldwide database to compensate for the region's lack of reported observations.

Volatile organic compounds (VOCs) have effects on the oxidative capacity of the lower atmosphere, air quality and radiative forcing, and are thereby contributing to climate change. To identify atmospheric trends in VOC abundance and composition, comparable datasets of atmospheric measurements at different spatial and temporal scales are needed. Traceability to the international system of units (SI) is key to achieve comparability. However, in many cases, this is hardly accomplished due to the lack of SI-traceable reference gas mixtures (RGMs) to calibrate the measuring instruments. Within the framework of the EMPIR project “Metrology for Climate Relevant Volatile Organic Compounds”, new SI-traceable RGMs of selected VOCs were prepared. The RGMs were produced at atmospheric amount-of-substance fractions (<100 nmol/mol) following different dynamic and static methods. For most of the selected compounds (halogenated VOCs and oxygenated VOCs, such as methanol, ethanol, and acetone), relative expanded uncertainties (U) lower than 5% were achieved fulfilling stakeholders’ needs. This was not the case for specific oxygenated VOCs (acetaldehyde; U < 10%) and terpenes (α-pinene, β-pinene, myrcene, and β-caryophyllene, U = 7–13%) because of surface reactions (e.g., adsorption) and impurities. Further development of passivation treatments, as well as closer collaboration among manufacturers, metrologists and atmospheric researchers are needed to facilitate the production of accurate, stable, and SI-traceable RGMs and to enhance, in turn, data comparability and climate trend identification.

This work investigates the spatio-temporal trends of air quality and its relationship with urban form in the Cergy-Pontoise conurbation from April 8 to June 6, 2022. Air quality data were obtained from a network of 16 PM10 and NO2 sensors, installed specifically to fill the information gap regarding pollution levels achieved in its different areas. The evaluation of the relationship between urban form and pollution identified different sources of pollution between PM10 and NO2. Morphological parameters such as building density, degree of openness to the sky, nature of the substrate, distances to roads, and traffic flow/speed were shown to influence the concentrations of each pollutant. Concerning the temporal variability, the daily amplitudes are well-marked. NO2 concentrations are higher during peak hours and lower in the middle of the day. In the evening, the concentrations slowly decrease until the early hours of the morning. The diurnal cycle of PM10 shows a high morning peak and a lighter one in the late afternoon. Unlike NO2, PM10 concentrations are higher during the day due to turbulence and pollen activity.

Heat content measured directly by ocean gliders in the Eastern Mediterranean (EM) Sea is compared to heat content inferred from remotely sensed sea surface properties, assuming a simple reduced-gravity model. Since the Middle East is one of the most responsive regions to climate changes, expected to be warmer and dryer, monitoring and studying the sea heat capacity and the effects on the local weather regime is of great importance. For example, EM heat content during fall was found to be significant in predicting the amount of precipitation over Israel in the following winter. Heat content is a function of both the mixed layer thickness and its mean temperature. Using temperature profiles observed by gliders, we can verify heat content inferred from remotely sensed sea surface temperature and sea level anomalies under reduced-gravity approximation and study its spatial and temporal variability. Sea gliders missions, conducted in high temporal resolution, provide detailed information on the water column thermal structure along its path. The comparison between the heat content obtained from gliders and the heat content calculated from remotely sensed properties shows that there are places and periods where a distinct separation between the surface and subsurface is found in the EM. This separation occurs when a subsurface dynamical eddy, e.g., is observed in the profiles collected by the glider but has no surface signature, hence is not detected by satellites. Furthermore, satellite products seem to poorly represent the heat content of coastal water which exhibit a different thermal structure than an open-water thermal structure. Another finding from the heat content comparison, obtained by two different methods, is that the subsurface is better represented by the surface during summer than during winter. This indicates that the strength of the stratification is also crucial when remotely monitoring heat content. In summary, heat content obtained directly by gliders, remotely by satellites, and the comparison between the two provides several important insights about water column thermal structure variability in one of the most sensitive regions to climate change. Ocean gliders mapping is needed when accurate heat content estimation is required.

Climate change raises several questions about its effects on a wide range of environmental factors. Forests are not immune to these effects, as the variability of rainfall over time affects several aspects, such as growth rate, water stress, regeneration, species composition and, possibly, population displacement. Assuming that the response of a tree species to climatic variability is territorially homogeneous within a common general trend may be erroneous. In fact, although the agglomerative hierarchical clustering technique revealed a certain similarity between the four weather stations analyzed, always greater than 0.62, both the amount of precipitation, and the similarity in the various months between them change, creating problems for the adaptation of silver fir especially in the summer season. With this in mind, it was also very important to evaluate through Fourier analysis possible cycles within the time series, in order to understand possible fluctuations that may influence the adaptation of the tree species analyzed. The annual precipitation required for a silver fir is over 1500 mm, and only one of the four rain gauges, the one with the highest altitude (Abetone, 2449 mm), is well above this threshold, while two others are well below (La Verna and Vallombrosa). Moreover, all the rain gauges investigated due to climate change show a significant trend (alpha level 0.05) of decreasing rainfall, which could lead to limitations in the growth of silver fir. The greatest problems occur in summer where the season is often dry and rainfall averages less than 200 mm at La Verna and Vallombrosa. This analysis is innovative, firstly because it identifies the recurring climatic and growth periods for the forest species in question, as well as understanding the influence that climate change has on vegetation in neighboring weather stations and assessing possible adaptation problems. This research can facilitate the development of strategies that favor the maintenance of environments. Therefore, effective adaptive forest management should take into account the variability of climatic factors at the local forest scale, as general models could be misleading.

Numerical methods represent a powerful tool for weather forecasting. However, they still face various limitations related to energy consumption and the time it takes to run simulations. To overcome these weaknesses, various statistical and deep learning models were developed to combine precision, time, and energy efficiency criteria. In this paper, we evaluated models of both classes for the task of short-term weather forecasting (one day, three days, and one-week forecasts), namely, the autoregressive integrated moving average, the theta method, and fast Fourier transform as statistical models, versus a long short-term memory, neural basis expansion analysis for interpretable time series, and temporal convolutional neural network as deep learning architectures. The dataset used in this study is sourced from the automatic meteorological station installed in the Marrakech region (center of Morocco) covering the period from January 3, 2013, to December 31, 2020, on a half-hour scale. These include air temperature (Ta), air relative humidity (Hr), and global solar radiation (Rg). Before feeding the data to our models, we first used the ERA5-Land Reanalysis data to impute missing values found in our time series. Results show that the TCNN model outperforms the others in terms of the coefficient of determination (R2) and the root mean square error (RMSE).

Atmospheric air pollution is one of the most critical environmental factors affecting the child, adolescent, and adult populations. Our research aimed to study the atmospheric air pollution effect on adolescents’ health risk. For that purpose, correlation analysis was used to reveal the relationship between atmospheric air pollution and adolescents’ health indicators. The Mann–Whitney test was applied for the comparison of the two samples’ distribution. We identified four districts in the city of Kazan for research: 1—Vakhitovsky, 2—Sovetsky, 3—Kirovsky, and 4—Privolzhsky districts. The target group of people was adolescents aged 15–17 years old, study period (2008–2019). Comparative analysis of the zones in the level of harmful substances in the air was performed. We presented the major air pollutants with significant differences (p < 0.05) in zoning (carbon (soot), carbon oxide, nitrogen dioxide, suspended particles PM 2.5 and PM 10, formaldehyde, benzol, and benzene). “From the health issues considered in this study—respiratory diseases (RD), allergic manifestations, anemias, congenital malformations (CM), and malignant neoplasms (NP)—RDs are at the top of the list: their proportion in primary morbidity structure varied insignificantly in all zones, the highest levels being found in the second zone. Analysis of chemicals’ content in atmospheric air showed that the third zone was in a worse position than the first and fourth zones. The second zone had the worst indices in significant evidence-based criteria. The current ecological situation in Kazan reflects the level of primary morbidity and prevalence of RD, NP, CM, and other adolescent diseases in the most neglected second and third city zones. Elevated concentration of formaldehyde, nitrogen dioxide, suspended particles PM 2.5, and benzol was observed in the second zone. Negative correlations between air pollutants and different human diseases, which can be explained by delayed body response to the accumulation of harmful substances, were also revealed in this zone. Suspended particles PM 2.5 and PM 10 have the strongest accumulative effect in this zone.

During the last decades, scientific interest in bromine (Br) has been fueled by its influence on the climate, namely via the depletion of ozone and elemental mercury. Today, there is compelling evidence that the heterogeneous/multiphase Br-reactive chemistry in the troposphere, extremely important in polar regions, is also abundant in other areas of the globe, including tidal coastal areas. This likely impacts the composition of wet precipitation for bromide (Br‒) and sustains Br transport over relatively large distances inland, enriching continental depositional environments. Thus, contributing to the quantification of Br‒ in rainwater concerning its main natural source (i.e., the ocean), and possible influential meteorological factors (e.g., wind speed/direction), seems important to better understand the role of the oceanogenic Br in paleoclimatology as a proxy for storminess. In this study, we used Br‒ concentrations ([Br‒]) in a set of twenty-one rainfall samples collected, on an event basis, between June 2018 and November 2019, at three sites in a coastal area of NW Portugal (Iberian Peninsula, IP; SW Europe), to investigate source–receptor relationships. The sampling sites were selected to represent a sea-to-inland gradient (~ 30 km long). Chemical analyses were performed by ion chromatography (anions) and inductively coupled plasma atomic emission spectrometry (cations). [Br‒] data, though without statistical outliers, showed high variability (12–375 µg/L), the median of the period being 155 µg/L, while the average of the recorded values was 161 ± 100 µg/L. In the sampling period, two [Br‒] peaks in rainfall were observed: in winter (January 30, 2019; 375 µg/L) and in summer (June 21, 2018; 329 µg/L), both at the innermost site. HYSPLIT model analysis suggests that the first event was related to air masses passing directly over the Atlantic before reaching the sampling area, while in the second, air masses arrived at the target region from the NE-to-E sector, after traveling through the IP landmass. PCA analysis (after z-score conversion of the values) allowed us to recognize three main groups of rainwater samples following similar tendencies on Br‒. It is expected that our results will be useful for ongoing and future research on (paleo)precipitation and (paleo)cyclogenesis.

Quasi-synoptic hydrological data collected in the Western Alboran Sea, during a glider cruise, dedicated to sample the Western Alboran Gyre (WAG) in late fall 2020 have been used to examine the distribution of the water masses in the region. The spatial variability has been addressed by means of a Support Vector Machine (SVM) classification applied on TS diagram through a training set of more than 3000 vertical profiles of temperature and salinity from the World Ocean Database (WOD). The training process is based on a manual labelling data in which the frontiers between the water masses have been defined on the basis of the values of temperature, salinity, and density, inferred from traditional expert analysis of the TS diagram in the area. Compared to conventional clustering analysis methods, this approach is appropriate to distinguish water masses in regions where intense mixing occurs such as the Alboran Sea. This new method highlights the WAG's characterization by recent AW advected from the Strait of Gibraltar, the presence of the Levantine Intermediate Water (LIW) in the northern two-third of the basin and the uplift of the dense Mediterranean Waters in the south, in the sill surroundings, roughly parallel to the Moroccan continental slope where they mix directly with AW.

Along the Moroccan coast, swell is generally unrelated to the weather on the coast. It is, most often, the consequence of barometric depressions passing between the Azores Archipelago and Iceland. North Atlantic swells are the most frequent, and they are characterized by fairly long wavelengths (period of 10–18 s) and are refracted on all or part of the continental shelf. In this context, the aim of the study is to compare Boussinesq and Birkhoff theories for the calculation of port agitation in two harbors: Casablanca and Jorf Lasfar. The comparison is done based on two models for the calculation of port agitation: The first model is based on the Birkhoff equation (MIKE 21 EMS) obtained from the potential swell theory, and the second is based on the Boussinesq equation (MIKE 21 BW). First, an analysis of agitation limit conditions for vessels in the ports is performed, then time series of offshore sea states are analyzed, and the propagation of the reconstructed sea states is performed, after which simulation scenarios are chosen. The research shows that Boussinesq waves are adequate to be used with long wavelengths swells and that Birkhoff theory MIKE 21 EMS is more pertinent to be employed in smaller coastal locations, where diffraction and wave breaking are critical, and the forcing wave conditions can be represented by a monochromatic and unidirectional wave. This phenomenon is important enough to be studied as it leads in guaranteeing good circulation conditions for ships which are very sensitive and important ships, and its simulation using pertinent theory helps provide optimal solutions leading to allow good harbor conditions.

The Portuguese Ocean Observing Program (OBSERVA.PT) under development at IPMA is presented. The activities started to be funded under two main projects: OBSERVA.PT that aims to implement appropriate technologies for monitoring the marine environment for the operational production of marine meteorological and oceanographic information. Meteorological and oceanographical equipment are being installed on cargo vessels, en route between Portugal Mainland and Madeira, Azores, and Cape Verde (NE Atlantic), as well as in fishing vessel; and OBSERVA.FISH that aims to develop a fully autonomous system to be installed on all types of fishing vessels, integrating various meteorological, oceanographical, and vessels behavior parameters. We will show the first results of the installation of a “ferrybox”-type (Undersee_water) equipment in a cod trawler vessel during her route from Portugal Mainland to the Grand Banks of Newfoundland. The “ferrybox” measured continuously temperature, salinity, chlorophyll, dissolved oxygen, pH, and turbidity from water pumped from the surface. The installation in the cargo and fishing fleet will allow the collection of data with great spatial coverage and high temporal resolution, difficult to obtain with other observation platforms.

This work employs a technique based on spatiotemporal projection onto a digital elevation model (DEM) to establish the geographical extent of exceptional sea levels. This makes it easier to study their influence. Using IPCC forecasts, maximum and extreme sea levels were computed for present and future (2100) time circumstances (RCP8.5). The characterization of the tidal components (astronomical amplitude and surge), the computation of the runup, and their statistical modeling according to the generalized extreme value theory (GEV) are all used in the calculation of these levels. The physical qualities of the shoreline are also taken into account while estimating the runup parameter (in particular the variation of beach slopes). The findings reveal that Ain Sbâa's shoreline is poorly protected from coastal flooding during powerful storms. The vulnerable areas are located near the industrial sector. The extension of potentially floodable areas would include areas of 10.9 km2 and 12 km2, respectively, with a maximum continental width of submersion between 1114 and 1225 m, according to projections of sea levels for present temporal circumstances and at the horizon of 2100. The static flood mapping methodology utilized in this “bathtub” has a number of flaws, including failing to account for the flows and time required to overflow the zones identified here as sensitive to flooding danger, but is widely used for coastal hazard maps. The highest values of the runup, the astrometric tide, the storm surge, and the sea level rise (SLR) are used in this approach's computations, with the chance of their coincidences remaining extremely low. This coincidence, though, is still imaginable.

Coastal flows are generally simulated by computer codes based on conventional discretization methods such as finite difference method, finite element method, or finite volume method. They are rarely simulated by the lattice Boltzmann method. The aim of this paper is to present the preliminary results of the numerical resolution of the Saint–Venant equations based on the new lattice Boltzmann method. The code thus developed was successfully applied to the real case of the Nador lagoon (Mediterranean cost of Morocco). It allows to reproduce with great precision the tidal flow in the lagoon generated by the main semi-diurnal wave M2. This method has the advantage of being fast since its implementation is much faster than the conventional methods mentioned above. With its parallel version on graphics processing unit, it can be adopted for simulations of phenomena requiring rapid responses such as flash floods.

Aerosols are short-lived atmospheric constituents, acting as climate forcers and accountable for major uncertainties in the total radiative forcing estimates, as reported by the Intergovernmental Panel on Climate Change (IPCC). Several aerosol microphysical, optical, and geometrical properties are measured at Évora ground-based station since 2002, using in situ instrumentation, as well as remote sensing techniques. Data obtained with sun photometers included in AErosol RObotic NETwork (AERONET) are analyzed here. The intra-annual variability of aerosol parameters is examined on a monthly basis, and the inter-annual trends are evaluated. Results show that the region is frequently affected by long-range transport of atmospheric aerosols from different origins as desert dust or forest fire, with higher aerosol optical depth (AOD) and lower Ångström exponent (AE) values in Spring and Summer with respect to Autumn and Winter. Trend analysis point to decreasing trends of AOD and AE during the 20-year period. However, when only extreme events are considered (AOD > 0.4), the AOD trend inverts and shows an increasing tendency at a rate of 1% per year, even more pronounced in Springtime at a rate of 2.9% per year, both trends statistically significant at the 95% confidence level. Aerosol radiative forcing (ARF) presents the lowest (more negative) values at the surface, and moderately low (negative) values at the top of the atmosphere, indicating a cooling effect at both levels, whereas a warming effect is obtained for the atmosphere. ARF values are consistent with aerosol properties measured and present significant trends indicating more pronounced effects of extreme events at all levels, especially during Winter and Spring.

The regional climate models are developed to assess the future trends of the climatic regimes and provide fine-scale information which is applied to check the vulnerability, impacts and adaptation in regard to climate change. The sub-tropical regions worldwide and specifically in Pakistan house a considerable diversity of faunal elements which is subjected to adverse impacts of climate change. Thus, we aim to provide here the details of upcoming climate change in sub-tropical regions of Pakistan (Chakwal and Jhelum) and its possible impacts on the recent mammalian communities of the area. For this purpose, different climatic models including RegCM4.4, CMIP5, and GCMs under the Coordinated Regional Climate Down-scaling Experiment (CORDEX) framework for the South Asian (SA) domain were used. We found that over the upcoming years (by 2099), the precipitation will slightly increase for a shorter Monsoon timespan, which may support a C3 ecosystem where browsers will be at an advantage (future Mean Annual Precipitation (MAP) > 900 mm/year). However, the current MAP is below 900 mm/year which supports a diversity of vegetation and available habitats to the mammals. Furthermore, a steady increase in the Mean Annual Temperature (MAT) was noted which may impact the faunal diversity of the region. The bovids, suids and rodents can bear the temperature elevation as they witness higher temperatures in other parts of the country as well. However, cervids in the region are already “nearly threatened” and may further be at a disadvantage due to climatic change and temperature elevation. The current MAT of the region is slightly below 22 °C; however, after three decades, it may rise above 25 °C ultimately threatening the extant diversity of the mammals of the region.

Utilizing the historical simulations from the Coupled Model inter-comparison Project Phase 6 (CMIP6), the contributions of greenhouse gasses, anthropogenic aerosols, and natural forcing to the declining trend in late summer precipitation over East Asia's transitional climatic zone (TCZ) were evaluated. Late summer precipitation across the TCZ has decreased significantly between the period of 1951 and 2013, as agreed upon by the gridded dataset utilized. CESM2, ACCESS-ESM1-5, GFDL-ESM4, and HadGEM2-GC31 out of the 13 estimated models capture the amplitude of the observed trend. Our results show that the decrease in precipitation across the TCZ is mainly attributable to the influence of aerosol forcing, which has a relative contribution of 139%. In comparison, greenhouse gases show an increasing trend in precipitation with a relative contribution of − 77%. We further examine the long-term trend in consecutive dry days during JAS and find that anthropogenic aerosol emissions significantly influence their occurrence. Our findings suggest that aerosols play a significant role in the observed changes in precipitation over the TCZ.

Atmospheric precipitation (rainwater, wet deposition) affected by industry is one of the sources of pollution that migrate to the ecosystem, especially by the uppermost soil layer and ground water. The chemistry of atmospheric precipitation around the ‘Miasteczko Śląskie’ zinc smelting plant (HCM) in the Upper Silesia region (southern Poland) was studied. The pH and chemistry of rainwater were analyzed with connection to the meteorological and climatic factors in the research area of the surrounded forest ecosystem area. Water samples were collected once per month (12 months in total) in 2021–2022 season at 20 monitoring points distributed in the grid (5 replications on each) located according to five modeled arches at the following distances from the main emission source: 1640, 2140, 2740, 3340, 3940 m. The control points were located opposite to the dominant wind direction (NW), and with wind directions in the distance above 6 km from the emitter. Pb, Zn, and Cd concentrations were found to exceed the Polish Environmental Protection Inspectorate reference data. Extremely high concentrations of pollutants were observed up to 3 km distance from the smelter: Cd (max. 1.43 mg L−1, mean 0.1) was higher, even than in the most polluted areas in the world (e.g., Mexico City), whereas zinc (max. 21.42 mg L−1, mean 1.71) and the Pb concentration (max. 0.44 mg L−1, mean 0.06) were similar to the highly polluted areas in the world. High concentrations of Cd, Zn, and Pb in rainwater indicate a strong industrial pressure in the adjacent forest ecosystem.

In this study, we investigated a relationship between integrated water vapor (IWV) and standardized precipitation index (SPI), focusing on historical drought events over the northern part of Africa from 1850 to 2014. Here, monthly data was obtained from two climate models of CMCC-ESM2 and CESM2, representative models in coupled model intercomparison project phase 6 (CMIP6). The IWV was standardized with the gamma distribution for various time intervals from 2 to 12 months, and the standardized IWV (IWVs) was compared with two established drought indicators, namely SPI-6 and SPI-12. We considered Pearson correlation coefficients for evaluating their relationship. As results of correlation analysis with SPI-6, Pearson correlation coefficients were larger than 0.74 from 2 to 4 months and lower than 0.41 from 9 to 12 months. However, the coefficients for SPI-12 with the time interval of 12 months were 0.82 and 0.71 for CMCC-ESM2 and CESM2, respectively, while showing negligible relationships with lower values than 0.21 from 2 to 4 months. It shows there are intra-seasonal and annual patterns in the relationship between IWV and SPIs. Further analysis of temporal patterns in IWV may lead to the potential for improved drought prediction.

The Canadian Prairies are identified as a potential climate change “hotspot” due to their relatively high latitude and central location on the continent. Agriculture is very vital in the southern part of the region, particularly the Prairie’s ecozone. Droughts are a frequent visitor in this region and so as floods from convective heavy precipitation events. Over a 24-h period, one single extreme precipitation event could deliver more than 25% of the mean annual precipitation. The behavior of extreme precipitation poses many challenges to flood management, adaptation, and coping mechanisms. The goal of this research is to uncover temporal and spatial aspects of 24-h maximum precipitation in the Canadian Prairie region, including change points, trends, long-term persistence, spatial correlation, upper tail properties, and any clustering to facilitate adaptation and coping mechanisms to extreme floods. 24-h precipitation data collected by tipping bucket rain gauges (TBRG) for 26 stations distributed across Alberta, Manitoba, and Saskatchewan provinces were used. We have investigated abrupt changes in the first two moments of the distribution by applying the Pettit test. The lag-1 (r1) serial correlation coefficient was used to calculate the auto- or serial correlation in the extreme rainfall datasets. The pre-whitening scheme was applied where there was statistically significant serial correlation before trend analysis. Nonparametric Mann–Kendall (MK) test and Theil-Sen’s slope estimator were applied for trend detection at 5% significance level. The presence of long-term persistence determined by estimating the Hurst exponent. Statistical modeling was conducted by applying the generalized extreme value (GEV) distribution. The results of the trend analysis suggest that the 24-h extreme precipitation trend is decreasing. Hurst exponent of > 0.5 was found in 65% of the stations demonstrating long-term persistence, while the remaining 35% showed no long-term persistence. In general, 24-h extreme precipitation in the Prairie region is heavy tailed as found in the GEV analysis. All three GEV parameters demonstrate a pronounced decreasing trend from the north to the south while plotted against latitude. Plotted map of 100-year return period values displays three clusters of high precipitation and flood vulnerable areas. One is in the northwest of Alberta and the other two in the South of Saskatchewan and Manitoba.

Rainfall onset and cessation are essential factors for the agrarian society in the West African Sahel region. This information determines crops to plant, helps project crop yields, and reduces loss due to climatic factors. Rainfall onset has also been associated with disease outbreaks; adequate knowledge will help in epidemiology and health management schemes. Therefore, predicting the onset will be necessary for the economy of countries in the Sahel region. Historical daily rainfall data from 1901 to 2000 for eight locations within the Sahel region were obtained from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) at a 0.5° × 0.5° grid resolution. Rainfall onset and cessation were determined using the Liebmann method based on long-term precipitation in the location of interest. Onset and cessation were predicted using a machine learning approach—Echo State Network. The root mean square error for rainfall onset was 15–24 days, while a range of 9–19 days was obtained for rainfall cessation. Results obtained in this study suggest that it is possible to effectively predict rainfall onset and cessation within the Sahel region. The predictions will enable farmers and government agencies to address agricultural, health, and environmental issues associated with the onset and cessation of rainfall in the region.

Primary biological aerosol particles (PBAP, also called bioaerosols) are airborne particles from integral or pieces of biological sources. The most abundant PBAP are bacteria, which have been shown in laboratory studies to have shown efficient ice nucleation activity (INA) in the atmosphere. Therefore, a significant amount of INA bacteria was found at ground level and in soil, indicating that those bacteria would percolate the soil layers to the underground and caves. Earth’s climate presented a high variability last millennia with two very distinct periods: the optimal medieval, from X to XII century (900–1100 DC), here after called Medieval Climate Optimum (MCO) and the Little Ice Age, from the XVI to XIX centuries (1560–1800), referred to as LIA. The MCO presented warmer climates, with less rainfall in Central Brazil and higher temperatures associated with more savanna types. In turn, LIA presented colder climates, with more rainfall in Central Brazil dominated by C3 plants and trees. Both periods are represented by a stalagmite from the Pau D’Alho cave, located at Central Brazil. The study goal aims to verify IN activity on the different layers of the Pau D’Alho stalagmite, focusing on MCO and LIA periods. This is a first study verifying INA in a stalagmite, for which it was necessary to develop a new methodology to approach it. The methodology was performed through smashing the stalagmite and taking the solution sample to a freezing bath, with and without diluting the preparation. The first results show, for temperatures warmer than − 10 °C, MCO presented 15, frozen tubes against only 6 from LIA, both without dilution. If they are bacterial, they likely were moved from land surfaces via percolation. Tests are colder temperatures might be effective in differentiating the activity in MCO stalagmites from that in LIA stalagmites.

The worldwide variations such as climate crisis and global warming are influencing considerably living species and earth due to their implication in the severity and rate of extreme weather. Thus, the seasonal precipitation prediction is of great importance due to the geographical, geomorphological, and seasonal characteristics of Atlantic and Mediterranean positions showing significant events impacting rainfall. In this research, we present a precipitation forecasting model based on multivariate time series where several factors affect the accuracy performance to mitigate extreme events induced by climate change. The purpose is to study the relationship between several climate variables, including surface pressure, wind speed, relative humidity, corrected precipitation, and temperature range, influencing precipitation and the design of an effective multivariate forecasting model showing the temporal evolution of different climate factors. Additionally, the prediction model was designed using a vector autoregression model and tested on monthly data collected from the NASA portal between 1981 and 2021. The introduced model extracts the variations of the time series characteristics and the interactive relationship of several related variables. We performed the Augmented Dickey-Fuller (ADFuller) test for stationarity and the cointegration causality test. The accuracy of the rainfall forecast model was evaluated using regression metrics, including mean absolute error, mean squared error, and root mean squared error, which showed effectiveness in predicting the monthly rainfall of Morocco. Our results showed a decrease in rainfall and a variation in the aridity index in Morocco between 1981 and 2021, reaching a peak in 1996 with a drought index value of 24.25 (semi-humid climate) and a minimum value in 2017 with an aridity index of 5.57 (arid climate). We conclude that during the twentieth and the beginning of the twenty-first centuries (1981–2021), Morocco experienced a change in climate levels from semi-humid to semi-arid and currently knows arid climate. Our model can capture real-world behavior, providing better forecasting performance, while the choice of the best lag value and the split interval of the time series is a challenging task.

Drought is a short- to long-term risk that challenges access to water. Prolonged droughts could inflict agricultural and economic losses and cause social hardships. Southern Canada is home to the majority of the country's population and serves as the country's primary economic hub. This region has more climatic diversity than the northern part and is prone to drought during the summer months. This study investigates the relationship between the occurrence of daily summer droughts and heat waves in southern Canada. In this regard, from 1985 to 2017, homogenized daily precipitation and maximum temperature data from 26 selected stations were used from May to September. Daily droughts have been calculated using the effective drought index (EDI). The threshold temperature for calculating heat waves was 32 ºC. We compared the results from southern Canada to those from the Prairie region. According to the findings, all types of daily droughts occur in southern Canada, but severe and extreme droughts are more common in the southern Prairies. Long-term daily droughts with the highest and lowest mean values were observed at the Toronto and St Jerome stations, respectively. Manitoba had the greatest variability in drought intensity between stations, with 1.96, and Quebec had the least, with 0.76. The increasing trend of daily droughts in Manitoba has been greater than in other southern Canadian provinces. The longest heatwaves occurred in Saskatchewan stations, with daily droughts intensifying in the long run.

The Mediterranean region is a highly fire-prone ecosystem with a long fire history, aggravated by the prevailing climate conditions (hot and dry summers) coupled with intensive land use. All forest fires in Israel are manmade, however, the weather conditions after ignition are crucial for its propagation. Given the recent increase in fire activity, the study explores Medium Time Scales (seasonal to annual) climatic variables affecting fire occurrences in Mt. Carmel and the Judean hills region, two ‘hotspots’ of frequent and devastating forest fires. The main climate variables for rapid forest fire propagation are very low relative humidity and above normal air temperature together with strong winds. Meteorological data for 1988–2019 were collected at two stations representing the weather conditions on Mt. Carmel and the Judean hills. During that period, data for all wildfires larger than 50 ha, on both sites, were obtained from the ‘Israel Fire and Rescue Services’. For each fire event, data included burnt area, exact location, date, fire duration and daily maximum temperature, daily minimum relative humidity, daily maximum wind speed and the wind direction during the maximum wind speed. The burnt area size was correlated with of relative humidity and air temperature departures, from the long-term average at the same time and location. Calculations were done for the day of the fire occurrence (day = 0) and for each day during the previous week (day =  −7 to day =  − 1). In Mt. Carmel, most forest fires (>50 ha) occurred in autumn (September–November), whereas in the Judean hills they occurred in summer (May–October). In summer, temperatures are at their annual maximum, a constant moderate sea breeze blows, and the fuel is relatively dry. However, while in Judean hills, relative humidity is at its annual minimum, on Mt. Carmel, in this period, relative humidity is at its annual maximum. This difference in the relative humidity regime between these two regions, apart from each other only by 120 km, is the leading cause of the difference in the timing of major forest fires. This method is already used for alerting of dangerous weather conditions that may result in a devastating forest fire.

The present work aims to highlight a particular event where there was a concomitance of particular hydrogeological and climatic conditions, unfortunately in a scenario which could be repeated. In fact, the south-eastern slope of Mount Vermenone (Central Apennines, Italy) was affected by a severe landslide movement of debris flow type. The phenomenon was triggered in the mid-high portion where a vast and thick debris accumulation (coarse, loose, and weakly cemented materials) was present. The aforementioned materials, in addition to being located on a steep slope, were frequently in a condition of water saturation during the winter, given the presence of springs and the characteristic impluvial form in which they were concentrated. In January 1997, a rapid snowmelt increased the water saturations in the thick debris, so that the materials became unstable on the slope and the movement is quickly activated. A fast and dense debris flow was triggered, moving along the steep slope down to the main valley floor: Here, the high energy flow did not stop but continued, spreading its accumulation almost to the built-up area. Only after several days and months the stream was able to resume its course, incising the huge mass of alluvial materials that can still be seen today at the edge of the plain. In addition, the groundwater resource also has been compromised as some springs in the area have changed their regime or even disappeared. The event was of considerable impact, and given its exceptional nature, studies on the dynamics of the landslide phenomenon were carried out. These in particular were conducted on the possibility of reactivations and also toward the monitoring of the adjacent areas. In this regard, a first response from the installed instruments was that no movement was recorded, and therefore, we are facing a very high threshold before triggering, probably due to the high permeability of the materials.

The identification of areas potentially subject to hydrogeological risk is an important issue, especially for Institutions that spend substantial sums each year on remediation. In 2018, north-eastern Italy was hit by an extreme event, Storm Vaia, which produced extensive damage, such as the collapse of trees and the reactivation of numerous landslide phenomena. In particular, the study area of this research, located in the municipality of Feltre, saw the reactivation of 9 landslide phenomena, which prompted the assessment of landslide susceptibility for the area in question. The objective of this research is to identify areas of high potential landslide hazard, using GIS-type software to prepare the spatial analysis and generating an algorithm inspired by the weight of evidence technique. For the calculation of susceptibility, eight environmental variables were considered, which can substantially influence the activation of landslide phenomena: permeability of the lithotype, type of vegetation cover, exposure, slope, ancient and stable deposits, recent slope deposits, bedrock, and existing landslides. The first level contains all the areas in which is present at least one of the conditions under our phenomena, the second at least two and so on. The algorithm works with three main processing tools, extraction by position, clip and merge, clipping the layers according to a number of simple combinations, without repetition, increasing for each susceptibility level: 8, 28, 56, and 70. The final map contains four levels of susceptibility in ascending order of hazard, and as further proof of the validity of the model it overlapped very well with already well-known and surveyed phenomena. The method used, unlike the weight of evidence, assigns the same weight to each underlying condition, so that the map can be more conservative and not underestimate risks. Potentially, the analysis could be further extended in the future by adding additional factors influencing slope stability, such as the amount of precipitation.

Afghanistan’s contribution to greenhouse gas emissions is negligible on a global scale however Afghanistan is adversely affected by the effects of climate change. Climate changes deeply affected Afghanistan’s natural resources, including water, agriculture, forests, pastures, rangeland, and ecosystems. Livelihoods are dependent on agriculture and create the basis of the country’s economy. Renewable energy sources, including hydropower, solar, wind power, and biomass is abundant, and their potential is much more than the national energy and electricity demands. The protracted war and political instability damaged the socio-economic and environmental infrastructure of the country. Therefore, Afghanistan mostly relies on energy transition from neighboring countries however the country possesses huge renewable energy resources. Also, renewable energy resource utilization greatly influences environmental and socio-economic development. In this study, it is investigated how renewable energy contributes to mitigating climate change in Afghanistan. Also, a rough estimation of renewable energy resources’ potential is conducted. In addition, the role of renewable energy resources in the sustainable development of the country is reviewed.

In order to meet the rising energy needs in South Asia as a result of population growth and societal development, the development of renewable energy is of paramount importance. With the hindcast data from the global atlas (GWA3 and Solargis) dataset, the aim of this study is to determine how climate change impacts wind power density (WPD) at 50 m above the ground level (AGL) through the power law method and photovoltaic (PV) potential over the subcontinent by using the climate change historical evaluation. The developing countries require the use of renewable energy, because of this, knowing the ideal location is important, and implementing wind and solar energy initiatives is crucial in this regard. The validation of GWA3 is based on the wind atlas methodology and the wind atlas analysis and application program (WAsP). Specifically, when analyzing threshold wind speed factors that influence wind energy production, according to the novelty of this research that applies the bias correction techniques quantile mapping based on Weibull distribution. Plus, global solar atlas uses Solargis PV modeling software and a high-resolution database of solar resources. The duration of data for wind energy and long-term reference data (ERA 5) is 2 and 12 years, respectively. In addition, overall subcontinent the average daily/yearly totals of solar PV plant that produces 1 kW-peak electricity, calculated for the period of 20 recent years. For WAsP modeling, the mean wind speeds of the predicted wind climates have an estimated ~ 6.5% standard uncertainty in the region of Pakistan and Maldives, and Bangladesh, respectively. For GWA3 modeling, the mean wind speeds of the predicted wind climates have an estimated mean absolute bias of 17% ± 8% and ± 2% standard deviation (assuming no bias or uncertainty on the WAsP modeling) in the region of Pakistan and Maldives, respectively. Moreover, for Bangladesh 1% ± 0 percent standard deviation is. Furthermore, in the simulation, losses due to dirt and soiling were estimated at 3.5%, while the total loss from all conversion losses was estimated at 7.5%. Another point worth mentioning was to estimate the energy density based on the data results on wind speed (m/s) at the hub height of 50 m AGL over the subcontinent. For instance, maximum and minimum energy density regions are Afghanistan and Maldives, respectively. Meanwhile, the PV system consists of crystalline silicon PV modules mounted at a fixed position, tilted to maximize yearly energy production. Consequently, understanding long-term WPD and PV power potential for micro-scale energy yields is crucial for understanding subcontinental variations. Additionally, the RE system reduces GHGs and limits global climate change. The CO2 can be switched to low with this method.

Global warming resulting from meteorological and oceanic perturbations manifests itself, among other things, in the rise of sea level and the increase in the energy of marine storms, as well as their frequency. The IPCC predictions put forward the probability of sea level rise (SLR), which could even exceed 1m by 2100 for the most pessimistic scenarios (i.e., RCP8.5). As a result, coastal erosion events will increase. Sandy coasts are generally considered to be sensitive to erosion and SLR. They become more vulnerable when they are heavily occupied by socio-economic activities and marine structures. To predict Agadir's bay shoreline movement due to erosion and sea level rise in the long term (2100), we used multi-date aerial photographs to initially deduct the historical rates of shoreline movement (1969–2016) and spatially delimit eroding areas and accreting areas, using Digital Shoreline Analysis System (DSAS). The calculated and geospatialised rates were then used to predict the displacement of the shoreline by 2100, using the empirical models of (Bruun in J Waterways Harbors Div 88:117–130, 1962) adjusted by Ferreira (2006) as well as the IPCC projections. The results show a considerable impact of marine structures on the erosion, balance and accretion processes along Agadir Bay (7 km), which reach 38%, 20%, and 42%, respectively. The shoreline prograde in the northern zone (1.35 m/year), and retreated in the south (− 1.54 m/year). Predictions of shoreline displacement by 2100 under RCP8.5 reveal a potential risk for tourist infrastructures bordering the sea (hotels, cornices, etc.) and call on coastal managers to develop protection and adaptation strategies. The predicted average setback rates of the shoreline are between − 16.8 m and − 33.7 m for 2050 and 2100, respectively, exceeding the width of the beach in several localities.