bluuebunny/crossref_metadata_2025 huggingface dataset:
MODEL PEMBELAJARAN DISCOVERY SECARA BLENDED LEARNING UNTUK MENINGKATKAN HASIL BELAJAR MATERI ASAM DAN BASA
Authors: SUKEMI SUKEMI
Published: March 2022

A teacher needs to strengthen a learning model that has been implemented by combining face-to-face learning (PTM) with online learning. This learning model is called blended learning. To find out the learning outcomes of the cognitive and psychomotor domains with this learning model, we conducted classroom action research with the title: Application of blended learning discovery learning model using Google Classroom to improve learning outcomes of acid and base material for class XI IPA SMA Negeri 3 Metro in the 2021 academic year. /2022. This research is classroom action research. The procedure is: the research is carried out in 3 cycles and each cycle has 4 stages of action, namely: planning, implementing, observing or testing, then reflection. An indicator of research success is an increase if learning outcomes are compared between cycles. The learning outcomes that we compare are the average and percentage of class completeness (PK) in the cognitive and psychomotor domains. The results of our study indicate that this class action can improve cognitive learning outcomes from an average of 53 to 70. The score of 70 is quite good. Class actions can also increase the Class Completeness Percentage (PK) from 23% to 53%. Psychomotor learning outcomes show that there is a percentage of class completeness (PK) equal to 99%, this number includes very good criteria.
ABSTRAKSeorang guru perlu memperkuat suatu model pembelajaran yang telah dilaksanakannya dengan cara menggabungkan antara Pembelajaran Tatap Muka (PTM) dengan pembelajaran daring. Model pembelajaran demikian ini disebut dengan blended learning. Untuk mengetahui hasil belajar ranah kognitif dan ranah psikomotorik dengan model pembelajaran ini maka kami melakukan penelitian tindakan kelas dengan judul: Penerapan model pembelajaran discovery secara blended learning menggunakan Google Classroom untuk meningkatkan hasil belajar materi asam dan basa kelas XI IPA SMA Negeri 3 Metro tahun pelajaran 2021/2022. Penelitian ini adalah penelitian tindakan kelas. Prosedurnya adalah: penelitian dilaksanakan sebanyak 3 siklus dan tiap siklus mempunyai 4 tahap tindakan, yaitu: perencanaan, pelaksanaan, observasi atau tes, lalu refleksi. Indikator keberhasilan penelitian adalah adanya kenaikan jika hasil belajar dibandingkan antar siklus. Hasil belajar yang kita bandingkan adalah rata-rata dan persentase ketuntasan kelas (PK) ranah kognitif dan ranah psikomotor. Hasil penelitian kami menunjukkan bahwa tindakan kelas ini dapat meningkatkan hasil belajar ranah kognitif dari rata-rata 53 dapat meningkat menjadi 70. Angka 70 masuk kriteria cukup baik. Tindakan kelas juga dapat meningkatkan Persentase Ketuntasan Kelas (PK) dari 23 % menjadi 53 %. Hasil belajar ranah psikomotor menunjukkan adanya persentase ketuntasan kelas (PK) sama dengan 99% angka ini termasuk kriteria sangat baik.
Sources of Surface O3 in the UK: Tagging O3 within WRF-Chem
Authors: Romero-Alvarez Johana , Lupaşcu Aurelia , Lowe Douglas , Badia Alba , Acher-Nicholls Scott , Dorling Steve R. , Reeves Claire E. , Butler Tim
Published: March 2022

Abstract. Tropospheric ozone (O3) concentrations are known to depend on a combination of hemispheric, regional, and local-scale processes. Estimates of how much O3 is produced locally vs. transported from further afield are essential in air quality management and regulatory policies. Here, a tagged-ozone mechanism within the WRF-Chem model is used to quantify the contributions to surface O3 in the UK from anthropogenic nitrogen oxide (NOx) emissions from inside and outside the UK during May–August 2015. The contribution of the different source regions to three regulatory O3 metrics is also examined. It is shown that model simulations predict the concentration and spatial distribution of domain-wide surface O3 with a mean bias of -3.7 ppbv. Anthropogenic NOx emissions from the UK and Europe account respectively for 13 % and 16 % of the monthly mean surface O3 in the UK, as the majority (71 %) of O3 comes from the hemispheric background. The north and the west of the UK experience the largest contributions from hemispheric O3 with peaks in May, whereas European and UK contributions are most significant in the east and south-east, intensifying towards June and July. It is demonstrated that more stringent emission controls over continental Europe, particularly in western Europe, would be necessary to improve health-related metrics, such as MDA8 O3 above 50 and 60 ppbv. Emission controls over larger areas, e.g., the northern hemisphere, are instead required to lessen the impacts on ecosystems as quantified by metrics such as the AOT40.
LED-based solar simulator to study photochemistry over a wide temperature range in the large simulation chamber AIDA
Authors: Vallon Magdalena , Gao Linyu , Jiang Feng , Krumm Bianca , Nadolny Jens , Song Junwei , Leisner Thomas , Saathoff Harald
Published: March 2022

Abstract. A light source has been built at the AIDA (Aerosol Interactions and Dynamics in the Atmosphere) simulation chamber at the Karlsruhe Institute of
Technology, simulating solar radiation at ground level. Instead of full
spectra light sources, it uses a combination of LEDs with a narrow emission
spectrum, resulting in a combined spectrum similar to the solar spectrum
between 300 and 530 nm. The use of LEDs leads to an energy-efficient, robust
and versatile illumination concept. The light source can be used over a wide
temperature range down to −90 ∘C and is adjustable in intensity and spectral width as well as easily adjustable to new technological
developments or scientific needs. Characterization of the illumination
conditions shows a vertical intensity gradient in the chamber. The integral
intensity corresponds to a NO2 photolysis frequency j(NO2) of
(1.58±0.21(1σ))×10-3 s−1 for temperatures
between 213 and 295 K. At constant temperature, the light intensity is
stable within ±1 %. While the emissions of the different LEDs
change with temperature, they can be adjusted, and thus it is possible to adapt the spectrum for different temperatures. Although the illumination of the
simulation chamber leads to an increase of 0.7 K h−1 of the mean gas
temperature, it is possible to perform experiments with aqueous droplets at
relative humidities up to ≤95 % and also above water or ice
saturation with corresponding clouds. Additionally, temperature- and wavelength-dependent photolysis experiments with 2,3-pentanedione have been
conducted. The photolysis of 2,3-pentanedione occurs mainly between 400 and
460 nm, resulting in a mean photolysis frequency of (1.03±0.15)×10-4 s−1 independent of temperature in the range 213–298 K with a
quantum yield of 0.36±0.04. In contrast, the yield of the two main photolysis products, acetaldehyde and formaldehyde, decreases with
temperature. Furthermore, the light source was applied to study the
photochemistry of aerosol particles. For the atmospheric brown carbon proxy
compound 3,5-diacetyl-2,4,6-trimethyl-1,4-dihydropyridine, photochemical reaction products were identified. In aerosol particles containing iron oxalate as a photosensitizer, the photosensitized degradation of organic acids (pinic and pinonic acid) was studied. Although the light source only
generates about one-third of the maximum solar irradiation at ground level at
Karlsruhe (49.007∘ N, 8.404∘ E; 12:00 UTC+2) on a clear summer day with a substantial intensity gradient throughout the simulation
chamber, it could be shown that this type of light source allows
reproducible experiments over a wide range of simulated atmospheric
conditions and with a large flexibility and control of the irradiation
spectrum.
Subtropical contribution to Subantarctic Mode Waters
Authors: Fernández Castro Bieito , Mazloff Matthew , Williams Richard G , Naveira Garabato Alberto
Published: March 2022

Subantarctic Mode Waters (SAMW), forming in the deep winter mixed layers in the Subantarctic Zone (SAZ) to the north of the Antarctic Circumpolar Current (ACC), connect the ocean thermocline with the atmosphere, contributing to ocean carbon and heat uptake and transporting high-latitude nutrients northward, to fuel primary production at low latitudes. Many aspects of SAMW formation are poorly understood due to the data scarcity during Austral winter. Here, we use biogeochemical Argo float observations to investigate the seasonal development, origin and significance of a subsurface salinity maximum in the SAMW formation regions. This conspicuous feature develops every summer in the seasonal thermocline of the SAMW formation regions as a consequence of the advection along the ACC of warmer and saltier waters from the western boundaries of the subtropical gyres, in particular the Agulhas Return current. The salinity maximum acts as a gatekeeper for SAMW ventilation, since it controls the seasonal evolution of stratification at the base of the mixed layer, modulating its rate of deepening during autumn and winter and re-stratifying the SAMW pool when winter mixing ceases. We also show that the subtropical influx, often overlooked, is key to understand the variability of SAMW properties, since it represents a leading order term in the heat and salt budgets at the formation regions. Finally, the analysis of the nitrate seasonal cycle at the SAMW formation regions as recorded by the Argo floats, revealed that the seasonal salinity increase goes along with a decrease in the concentration of this nutrient, as a consequence of the advection of subtropical waters containing low preformed nitrate. These results suggest that nutrient concentration in SAMW is controlled not only by the rate of upwelling of high-nutrient waters south of the ACC and the degree of biological drawdown during their northward transit, as frequently assumed, but also by the influx of subtropical waters, pointing to previously overlooked feedbacks in the redistribution of nutrients between high and low latitudes.
Eichhornia crassipes macrophytes for treatment of heavy metal contaminated water
Authors: Anuradha Anuradha , Yadav Brijesh Kumar
Published: March 2022

Heavy metal contaminated water is a major threat to human and aquatic life. Chromium is a toxic heavy metal discharged into surface water mainly due to industrial applications. Physico-chemical technologies to treat chromium-contaminated waters are expensive, especially for developing countries. Macrophytes-based phytoremediation is a competent method of water treatment that is simple, cost-effective, and provides satisfactory results. In the present study, we investigated the potential of macrophyte Eichhornia crassipes, commonly known as water hyacinth, to accumulate chromium concentrations from water. We conducted a hydroponics experiment for ten days under controlled laboratory conditions to examine the hyperaccumulation potential of the species. The experiment results showed that Eichhornia crassipes is an excellent accumulator of chromium. The maximum concentration was found in the plant's roots with small amounts in the shoots and leaves. These results demonstrate that E. crassipes can provide an efficient and environment-friendly option of remediating chromium-contaminated surface water bodies.
Characterizing social vulnerability for climate impact assessment at global scale
Authors: Reimann Lena , Koks Elco , de Moel Hans , Aerts Jeroen
Published: March 2022

Every year, extreme events caused by climate-related hazards result in severe impacts globally. These impacts are expected to increase in the future due to both climate change and population growth in exposed locations. However, impacts are not only driven by exposure to extreme events, but also by the population’s vulnerability to these hazards, determined by individual characteristics such as age, gender, and income. Thus far, global-scale climate risk assessments account for social vulnerability to a limited degree. To address this gap, we produce spatially explicit global datasets of variables that can be used for characterizing social vulnerability. We further combine these data into a globally consistent and spatially explicit Social Vulnerability Index (SoVI), which will be made publicly available along with the input variables. To explore the value of the SoVI in characterizing social vulnerability, we validate it with the observed impacts (e.g., fatalities, damages) of past extreme events. To do so, we overlay the spatial vulnerability characteristics with recently published flood maps of observed flooding events across the globe, also testing how each vulnerability variable performs individually in explaining the observed impacts. Our analysis helps to develop a more in-depth understanding of the characteristics that drive social vulnerability globally, along with their spatial distribution. Therefore, our results can support decision-making in developing strategies that reduce social vulnerability to climate-related hazards, for instance related to spatial planning, socioeconomic development, and adaptation.
CORDEX-SA Regional Climate Model Ensemble Performance Evaluation and Future Climate Change over India
Authors: Singh Saumya , Mall Rajesh Kumar
Published: March 2022

The present study aims to analyse future changes in mean maximum and extreme temperature over India using 17 regional climate simulations from  CORDEX-SA experiment RCM ensembles at a spatial resolution of 0.5° x 0.5° for mid-term (2041-2060) and long-term (2081-2099) future under RCP 4.5 and RCP 8.5 scenarios. The regional climate simulations of the three RCM ensembles namely IITM-RegCM4, SMHI-RCA4 and MPI-CSC-REMO2009 were first evaluated against observed seasonal maximum temperature (Mar-Jun) during historical period (1971-2005). The datasets were obtained from CCCR-IITM ESGF data node for the study period. The model performance was assessed using standard performance measure statistics such as mean absolute error, root mean square error, mean bias, percentage bias. The RCMs show warm and cold bias in simulating the climatological mean maximum temperature with mean bias ranging from to 8.43°C(warmest) to -37.29°C (coldest) by CNRM-CM5 RCM of IITM-RegCM4 ensemble and by CSIRO-Mk3.6 RCM of SMHI-RCA4 ensemble respectively over the country. Variance scaling bias correction method was applied to correct the bias associated with the RCMs which significantly reduced the RMSE of RCMs from 11.03 (SMHI-RCA4) and 9.17 (IITM-RegCM4) to around zero after bias correction. Future changes assessed in mean maximum temperature show an increase in the range of 0.5°C to 4.5°C during mid-term (2041-2060) and 0.6°C to 5.84°C long-term (2081-2099) future period while under RCP 8.5 the increase ranges from 0.88° C to 5.40° C for mid-term (2041-2060) and 1.31° C to 12.87° C for long-term (2081-2099) period. The most pronounced increase is observed in the northern, eastern and north-eastern region of the country in which highest rise was simulated by IPSL-CM5A-MR(SMHI-RCA4) in northern region of the country for both the scenarios. The study also analyses changes in different ET-SCI indices as a measure of extreme temperature which have increased multi-fold in the future over the country. The study identifies the regions and magnitude of significant climate change signal expected in the mean maximum and extreme temperature in the future. It enhances the understanding and quantification of inter-model uncertainties within CORDEX-SA experiment RCM simulations. The outcomes of the study have both scientific and societal values in building resilience and informed efforts to avert the severe implications posed by increasing extreme temperature and heat events over India.

 

Keywords: Future Climate Change, CORDEX-SA, Regional Climate Model, Bias Correction, Extreme weather events
Aufeis impact on the hydrological cycle in the North-Eastern Russia
Authors: Nesterova Nataliia , Makarieva Olga , Ostashov Andrey , Zemlyanskova Anastasiya , Shikhov Andrey , Alexeev Vladimir
Published: March 2022

Aufeis are produced annually in the rivers valleys in permafrost environment as the result of layer-by-layer freezing of groundwater flowing to the surface. Aufeis are widespread in the territory of the North-East of Eurasia (including the basins of large rivers in permafrost, such as the Yana, Indigirka, Kolyma, Anadyr, Penzhina Rivers and rivers of the Chukchi Peninsula (total area about 2 mln. km2).  They comprise an important water resource of the study region.

Based on the analysis of Landsat satellite images for the period 2013-2019 the number and total maximum area were estimated. As Landsat images do not always allow correctly assess the maximum area of aufeis, it was adjusted to get the maximum value before the beginning of ablation period for the assessment of aufeis resources. Total number of giant aufeis (>0.1 km2) formed by groundwater reaches 6217 with maximum area of about 4500 km2 (in average 0.22 % of studied area). For each aufeis field the assessment of maximum ice reserves was conducted.  

The aufeis resources of the North-East are at least 10.6 km3 or 5 mm of aufeis runoff. The aufeis resources vary from 0.4 to 4.25 km3 (or 3.7 – 11 mm) for individual basins of large rivers. The greatest aufeis resources in absolute values are found in the Indigirka River basin. The contribution of aufeis runoff to streamflow in different seasons was calculated for 58 hydrological gauges (area 523 – 526000 km2). Aufeis annual runoff varies from 0.3 to 29 mm (0.1 – 22%, average 3.8%) with the share in winter runoff amount about 6 – 712 % (average 112%) and the spring freshet 0.2 – 43% (average 7.1%).

The influence of aufeis and glaciers on the water balance is compared – in general, the aufeis runoff exceeds the glacial runoff. The response of aufeis to climate change depends on different factors of the natural system. The dynamics of aufeis formation is directly related to the winter runoff, which changes are observed in different parts of the cryolithozone. The presented results are relevant for studying the impact of climate change on the hydrological cycle and its components in the permafrost regions of the Northern Hemisphere.

The study was carried out with the support of RFBR (19-55-80028, 20-05-00666) and St. Petersburg State University (project 75295879).
Tools to develop environmental flow guidelines in an uncertain future hydrological context
Authors: St-Hilaire André , Berthot Laureline , Ferchichi Habiba , Caissie Daniel
Published: March 2022

Environmental flows (eflows) refer to the amount of water required to sustain aquatic ecosystems. In its formal definition, three flow characteristics are listed that need to be minimally maintained: quantity, timing and quality. Ssome of the current tools used for eflow determination in the context of an evolving climate are based on hydrological metrics. Some of the potential caveats associated with their usage are caused by the fact that flow time series are increasingly non-stationarity. Timing of low flow events will also likely change within a season, but will also likely shift in seasonality in some regions. Flow quality is a multi-faceted concept. It is proposed that a first simple step to partly incorporate flow quality in future analyses is to include water temperature as a covariate.  An example of this combination of flow and temperature is provided for Eastern Canada.
Western shifting of Extreme Rainfall Events over the different Indian River Basins in the last 119 years
Authors: Chaubey Pawan Kumar , Mall Rajesh Kumar
Published: March 2022

India experienced more flood situations due to the increasing extreme rainfall events over the different Indian River Basins (IRBs) during the last few decades. An Extreme Value Theory (EVT) is used to examine trends of rainfall extremes over the IRBs using long-term observed high-resolution grid-based rainfall (1901-2019) of the India Meteorological Department. The analysis depicts that when generalized extreme value theory (GEV) is applied to annual maximum rainfall over IRBs, statistically significant uniform trends were not seen. The spatial variations in the annual maximum rainfall for the 10-, 30- and 100-year return levels show statistically significant increasing trends over the IRBs. The shifting trend of rainfall extremes from northeast towards the western river basins of IRBs in the last two decades and resulted in damage to life and property on the west coast. The decadal changes in average intensity of dry and wet condition at 12- months running time window reveals that the shifting and increasing pattern of the rainfall extremes events during the last decades of the 20th century (1981-2000) and current decades of the 21st century (2001-2019) over the western ghats and west-flowing river basin leads to several floods situations. This research highlights the significant increasing trend in extreme rainfall events over the IRBs, which may pose a grave risk to agriculture, human life, and predominantly on the vulnerable sections of the society.
Exploring the mechanical influence of mush poroelasticity on volcanic surface deformation 
Authors: Alshembari Rami , Hickey James , J. Williamson Ben , Cashman Katharine
Published: March 2022

Understanding the mechanical behaviour of melt reservoirs is vital for advancing geophysical models that aim to constrain the evolution of subvolcanic systems and inform hazard monitoring and mitigation. From geophysical and petrological studies, large melt-dominated (magma) reservoirs are difficult to sustain over long periods of time. Melt is more likely to reside within reservoirs which consist of variably packed frameworks of crystals, so-called crystal mush, as well as in pockets of magma, in changing proportions over time. The behaviour of crystal mush, in particular, is emerging as a vital consideration in understanding how magmatic systems evolve. In addition, current models for volcano deformation often consider static magma sources and thus provide little insight into the internal dynamics of melt reservoirs; and these models ignore the presence of crystals and therefore the likely poroelastic mechanical response to melt intrusion or withdrawal. Our study considers the melt reservoir to be partly crystalline (> 50% crystal fraction), with melt residing between crystals. We examine the influence of poroelastic mechanical behaviour on the evolution of reservoir pressure and the resultant surface deformation. From our results, the modelling of a crystal mush rather than a 100% melt magma reservoir can significantly modify the resulting spatial and temporal mechanical evolution of the system. Specifically, the poroelastic behaviour of a mush reservoir will continue to develop following the end of a melt injection period, generating further time-dependent surface displacements. Post-injection and post-eruption inflation can occur, which are linked to a poroelastic response associated with continuous melt diffusion. Following an injection/eruption, a steady-state point is eventually achieved when the fluid pressure reaches a uniform value throughout the reservoir. This process is controlled by the poroelastic diffusivity. Increasing the reservoir crystal fraction from 50% to 90% reduces the mobility of melts, decreases permeability, and leads to a slow rate of melt diffusion. Our study confirms that volcanic surface deformation can occur without continued intrusion or withdrawal of melt.
Stable water isotopes to understand sources, pathways and ages of water in complex urban settings
Authors: Marx Christian , Tetzlaff Dörthe , Hinkelmann Reinhard , Soulsby Chris
Published: March 2022

The hydrology of major cities is controlled by complex networks of both natural and engineered flow paths and characterised by spatio-temporal variations in connection and disconnection of water sources. Here, we traced the transformation of stable water isotopes through the urban critical zone, in Berlin, Germany. The Panke catchment is heavily influenced by a wastewater treatment plant (~700,000 inhabitants), and legacy effects of water management during the past century. Two and a half years of daily stream isotopes revealed the complicated interactions between the groundwater fed-stream and urban impacts, such as wastewater effluents and “imported” transboundary water sources, and urban stormwater overflows. To mitigate the effects of the latter, urban greenspaces are important to store and release water more naturally to imitate the “sponge-city” concept and retain water in the urban landscape. We therefore also investigated stable water isotopes at the plot scale in three parks in Berlin. We sampled grassland and urban forest sites during the dry year of 2020. Soil and xylem isotopes of different tree species and under grassland revealed shallower root water uptake from grasslands and greater recharge by younger waters. As evapotranspiration accounts for about 90% of rainfall, ecohydrological dynamics in urban green spaces were shown to be largely disconnected from urban runoff generation. Isotopes were shown to be invaluable tools in multi-scale understanding of urban hydrology and have great potential in contributing to the evidence base needed to develop policies for more sustainable urban water management in the face of increased urban growth and climate change.  
Modulation of Dry and Wet Period Temperatures in India
Authors: Prabhakar Anagha , Mitra Subhasis
Published: March 2022

Temperature-based events such as heatwaves and compound dry hot extremes impact the socio-economic sectors of a nation. In this study, the differential rates of temperature intensification across different seasons and regions in India coupled with dry/ wet climatologies are studied. The analysis is done for both historical observations and future CMIP6 simulations. Further, the temperature intensification rates were linked to established atmospheric feedback mechanisms. Results show that observed temperature intensification rates are positive/negative during dry/wet climatology relative to average climatology. Analysis of feedback mechanisms showed that cooling temperature trends are associated with a decrease in atmospheric aridity (vapor pressure deficit) and an increase in relative humidity. While in southern India, temperature trends are similar for all three climatologies (average, dry, and wet), albeit with different rates of intensification, in northern India, the temperature intensification shows notable contrasting trends during dry and wet climatologies. The highly irrigated Indo-Gangetic Plain region in northern India is found to experience significant cooling temperature trends during dry climatology and these trends are much more prominent during the agricultural Rabi season. Climate change analysis using CMIP6 simulations indicates further exacerbation of temperatures across all regions in the Indian subcontinent and foresees an increased probability of compound extremes in the future.
Sensitivity of PET estimation methods towards drought characterization under climate change in the Indian subcontinent 
Authors: Varghese Femin C , Mitra Subhasis
Published: March 2022

In the Indian subcontinent, the uncertainty associated with potential evapotranspiration (PET) over drought characterization is inadequately studied. This study was conducted to understand the sensitivity of PET estimation methods towards drought characterization using multiple PET-based drought indices under future climate change. We used eleven PET estimation methods (Blaney-Criddle (BC), Hamon (HM), Hargreaves (HG), Kharrufa (KF), Thornwaithe (TW), Dalton (DN), Meyer (MR), Irmak-Rn (IRN), Irmak-Rs (IRS), Priestley-Taylor (PT), and Penman-Monteith (PM)) for the future period (from the Coupled Model Intercomparison Project 5). Further, for drought characterization six PET-based drought indices are utilized in this study: the Standardized Precipitation Evaporation Index (SPEI), the Supply-Demand Drought Index (SDDI), the Reconnaissance Drought Index (RDI), the self-calibrated Palmer Drought Severity Index (sc-PDSI), the Standardized Moisture Anomaly Index (SZI), and the Standardized Palmer Drought Index (SPDI). We also employed a variance-based global sensitivity analysis to determine the relative sensitivity of projected drought indices to the GCM and PET estimation methodologies under climate change scenarios. Results indicate that different PET-based drought indices show vastly different drought projections for the future, which is highly influenced by the PET methods. Overall, SPEI and SDDI produce comparable results, indicating an increase in future drought estimates compared to the rest (RDI, SPDI, SZI, and sc-PDSI). The TW method reported higher drought projections compared to other PET methods irrespective of the drought indices.  This is due to the fact that the TW method also showed the highest increase in PET compared to the rest of the methods. Results from the sensitivity analysis indicate that all the drought indices are more sensitive to the choice of PET methods compared to the GCM. However, analysis was done after excluding the TW approach significantly altered the sensitivity, and GCMs were found to be more sensitive compared to PET methods. The results from this study reveal that drought projections derived from multiple PET estimation methodologies indicate drier conditions in the future, albeit at variable levels. Thus, the selection of the PET estimation method and drought index will be crucial in the Indian subcontinent for future drought investigations.
Geomorphic characterization of the Lower Niger River using Google Earth Engine 
Authors: Olusola Adeyemi , Boothroyd Richard , Adelabu Samuel
Published: March 2022

The Niger River, the third-largest river on the African continent with a length of about 4,200 km, is a major transboundary river that flows through 9 countries. It is a mainstay of the economy in West African countries with over 20 million people directly or indirectly depending on it for their livelihoods. Although the geomorphology of the Niger Delta is well studied, comparatively little is known about the fluvial portions of the system, despite their considerable value to local communities. Here, we focus on a ~100 km braided segment of the Lower Niger River located between Lokoja and Idah, downstream of the Niger-Benue confluence in south-central Nigeria. The hydrogeomorphology of the segment is largely controlled by the Kainji Dam (Niger tributary) and the sediment supplied from the Benue catchment (Benue tributary). Our study aims to assess changes in river planform by applying semi-automated satellite imagery analyses. We use the cloud-based computing platform Google Earth Engine (GEE) to analyse multi-temporal collections of Landsat, Sentinel and Planet satellite imagery acquired between 1987 and 2021. At decadal time intervals, we classify the active river channel (including water and exposed alluvial deposits) using a HSV colour representation of the RGB imagery, combined with conventional multispectral indices. We quantify areas of erosion and accretion to identify laterally dynamic reaches during the analysis period. We link these findings to changes in the hydrological regime using discharge estimates from nearby gauging stations. Findings are useful for predicting and building resilience to river-related hazards in dynamic landscapes and will support sustainable river management interventions in the area.
Matched Field processing for complex Earth structure
Authors: Schippkus Sven , Hadziioannou Céline
Published: March 2022

Matched Field Processing (MFP) is a technique to locate the source of a recorded wave field. It is the generalisation of beamforming, allowing for curved wavefronts. In the standard approach to MFP, simple analytical Green's functions are used as synthetic wave fields that the recorded wave fields are matched against. We introduce an advancement of MFP by utilising Green's functions computed numerically for real Earth structure as synthetic wave fields. This allows in principle to incorporate the full complexity of elastic wave propagation, and through that provide more precise estimates of the recorded wave field's origin. This approach also further emphasises the deep connection between MFP and the recently introduced interferometry-based source localisation strategy for the ambient seismic field. We explore this connection further by demonstrating that both approaches are based on the same idea: both are measuring the (mis-)match of correlation wave fields. To demonstrate the applicability and potential of our approach, we present two real data examples, one for an earthquake in Southern California, and one for secondary microseism activity in the Northeastern Atlantic and Mediterranean Sea. We provide an accompanying simple code example to illustrate the method on github.
Detection of nonlinear kinematics in InSAR displacement time series for hazard monitoring
Authors: Bovenga Fabio , Refice Alberto , Argentiero Ilenia , Nutricato Raffaele , Nitti Davide Oscar , Pasquariello Guido , Spilotro Giuseppe
Published: March 2022

Multi-temporal SAR interferometry (MTInSAR),  allows analysing wide areas, identifying critical ground instabilities, and studying the phenomenon evolution in a long time-scale.  The identification of MTInSAR displacements trends showing non-linear kinematics is of particular interest since they include warning signals related to pre-failure of natural and artificial structures. Recently, the authors have introduced two innovative indexes for characterising MTInSAR time series: one relies on the fuzzy entropy and measures the disorder in a time series [1], the other performs a statistical test based on the Fisher distribution for selecting the polynomial model that more reliably approximate the displacement trend [2].

This work reviews the theoretical formulation of these indexes and evaluate their performances by simulating time series with different characteristics in terms of kinematic (stepwise linear with different breakpoints and velocities), level of noise, signal length and temporal sampling. Finally, the proposed procedures are used for analysing displacement time series derived by processing Sentinel-1 and COSMO-SkyMed datasets acquired over Southern Italian Apennine (Basilicata region), in an area where several landslides occurred in the recent past. The MTInSAR displacement time series have been analysed by using the proposed methods, searching for nonlinear trends that are possibly related to relevant ground instabilities and, in particular, to potential early warning signals for the landslide events. Specifically, the work presents an example of slope pre-failure monitoring on Pomarico landslide, an example of slope post-failure monitoring on Montescaglioso landslide, and few examples of structures (such as buildings and roads) affected by instability related to different causes.

References

[1] Refice, A.; Pasquariello, G.; Bovenga, F. Model-Free Characterization of SAR MTI Time Series. IEEE Geosci. Remote Sens. Lett. 2020, doi:10.1109/lgrs.2020.3031655.

[2] Bovenga, F.; Pasquariello, G.; Refice, A. Statistically‐based trend analysis of mtinsar displacement time series. Remote Sens. 2021, doi:10.3390/rs13122302.

Acknowledgments

This work was supported in part by the Italian Ministry of Education, University and Research, D.D. 2261 del 6.9.2018, Programma Operativo Nazionale Ricerca e Innovazione (PON R&I) 2014–2020 under Project OT4CLIMA; and in part by Regione Puglia, POR Puglia FESR-FSE 204-2020 - Asse I - Azione 1.6 under Project DECiSION (p.n. BQS5153).
Using CubeSats to develop critical thinking skills 
Authors: Damas M. Chantale
Published: March 2022

Providing students with hands-on experience in emerging technologies, and engaging them in discovering new knowledge are ongoing challenges in undergraduate engineering and science education. CubeSats are playing an increasingly significant role in scientific research and exploration, as demonstrated by NASA’s successful Insight Mission. Challenging students to design, build, and test these small satellites has the potential to increase their problem-solving, computational, and critical thinking skills.  Furthermore, since CubeSats can be built with commercial-off-the shelf (COTS) components, they are relatively inexpensive and accessible to a diversity of programs and students.  This work describes a successful program in which students were challenged to design, build, and test a 1U (unit) COTS CubeSat. CubeSat student projects incorporate both technology demonstrations and sensors as scientific payloads.  Programmatic and technical successes and challenges faced by students especially during the COVID-19 pandemic are discussed, and some strategies are offered on how to implement such a program at different institutions with diverse student populations.
Response of the Caspian Sea Shoreline to hydro-climatic Drivers Variation
Authors: Akbari Mahdi , Klöve Björn , Faramrazzadeh Omolbanin , Torabi Haghighi Ali
Published: March 2022

During the past three decades, seawater level (SWL) in the Caspian Sea has declined by about 2 m, and sea area has decreased by about 15 000 km2. This has affected coastal communities, the environment and economically important sea gulfs (e.g., Dead Kultuk). We simulated SWL using total inflow from feeder rivers and precipitation and evaporation over the sea to assess the effects of coastline change and evaluate zones vulnerable to desiccation. We determined the potential of coastal vulnerability over the past 80 years by comparing the minimum and maximum annual water body maps (for 1977 and 1995). We then determined the linear regression between SWL rise and covered potential vulnerable area (CVA), using annual Normalised Difference Water Index (NDWI) maps and SWL data from 1977 to 2018. Combining SWL-CVA regression and SWL simulation model enabled us to determine desiccated areas in different regions of the Caspian Sea due to changes in precipitation, evaporation and total inflow. The results showed that 25 000 km2 of the sea is potentially vulnerable to SWL fluctuations to be desiccated. Also, we found 70% of this vulnerable area is in Kazakhstan. Potential vulnerable area per kilometer coastline was found to be 6 km2 in Kazakhstan, 4 km2 in Russia and the whole of the Caspian Sea, 1.5 km2 in Iran, 1 km2 in Azerbaijan, and 0.5 km2 in Turkmenistan. The results also indicated that SWL in the Caspian Sea is sensitive to evaporation and that, e.g., a 37.5 mm decrease in mean annual net precipitation would lead to an 1875 km2 decrease in the sea area, while a 1 km3 decrease in mean annual inflow would lead to a 1400 km2 decrease in the sea area. Thus the developed framework enabled the spatial consequences of changes in water balance parameters on sea area to be quantified. It can assess future changes in SWL and sea area due to anthropogenic activities and climate change.
Assimilation of EO based data into LSM to compute the contribution of snowmelt to discharge in the High Mountainous Region.
Authors: Maurya Vikrant , Gupta Manika , Pant Naresh Chandra , Sahai Atul Kumar
Published: March 2022

The cryosphere is an important component of the Earth’s climate system and is exceptionally sensitive to global warming. Studies have shown the decline in the ice and snow cover with increasing temperatures in the Himalayan Mountainous Region (HMR), the third-largest deposit of ice and snow. The melting of ice and snow contributes to the discharge and affects the availability of water in the downstream areas. The introduction of satellite-based observations in conjunction with land surface modelling is paramount as the scarcity of ground data in the mountainous region limits the study.

The study focuses on the snowmelt contribution of the HMR to the discharge of Ganga Basin. An integrative approach of NASA Land Information System Framework (LISF)-NOAH Land Surface Model and Runoff Routing Model is used to estimate the snowmelt contribution to discharge. The snowmelt contribution has been compared for the period 2008-2018 based on two model runs, i.e., control with experiment run wherein satellite-based snow cover observations (MODIS) has been assimilated in the model based on Direct Assimilation (DA). Assimilation of snow cover data helps to model the snowmelt efficiently as compared to control run which is then used to simulate discharge and snowmelt contribution to discharge.

The simulated DA mode results are more congruous with the station observed data and is helpful in producing a snowmelt baseline for the HMR. The snowmelt baseline can be used for comparing future snowmelt contributions to discharge in the context of environmental change.
Application of Template Matching to OBS array observation in Orca Volcano (Bransfield Strait, Antarctica)
Authors: Seivane Helena , Martín Rosa , Almendros Javier , Wilcock William , Soule Dax
Published: March 2022

The temporary seismic network deployed from January 2019 to February 2020 in the Bransfield Strait as part of the BRAVOSEIS project has enabled the development of an earthquake catalogue for Orca submarine volcano. A STA/LTA algorithm, manual picking, and the HYPO71 location algorithm with a 1-D model based on previous studies was used to create a catalogue of 4988 earthquakes. The seismicity was characterized by low magnitude events (-1<ML<2.7) occurring mainly in the upper five-kilometers around Orca caldera. Declustering using the Gardner and Knopoff method, reduced the catalogue size by nearly 90%. The declustered catalogue is complete above a magnitude ML of 0.9 and the estimated b-value for the whole period studied is 1.03 +/- 0.18. Because of the noisy the oceanic environments, building the catalogue became an arduous task to perform manually even with a STA/LTA algorithm. Having catalogued such a numerous microseismic events and with the goal of enhancing the catalogue, we apply a super-efficient cross-correlation (SEC-C) method on the continuous network dataset. The effectiveness of SEC-C is soon corroborated by analysing the output of this template matching-based detector. A volcano-tectonic swarm previously catalogued manually between July and August 2019 is clearly identified by the preliminary results of the SEC-C method. The thresholds we imposed for the cross-correlation values and signal-to-noise ratios considered for the workflow from event detection to location were chosen to make the method as ‘blind’ as possible. More than six hundred events have been incorporated after the template matching procedure, considerably augmenting the catalogue.
Simulating the contribution of groundwater to crop growth at the global scale
Authors: de Graaf Inge , Nauta Lisanne , Droppers Bram
Published: March 2022

Groundwater is the largest available freshwater resource on earth and is critical for people and the environment. Irrigation is by far the largest groundwater user worldwide. In many of the intensively irrigated areas, more groundwater is used than replenished by rainfall or infiltrating streamflow. As a result, groundwater levels are dropping, leading to reduced dilution of pollutants in streamflow, drying of rivers and wells, land subsidence, salt intrusion, and groundwater depletion. In the coming decades, global food demands will increase and a major challenge lies ahead of how to ensure sufficient regional and global food availability in a sustainable way. It is expected that agriculture will increasingly depend on groundwater to support the required increase in crop production. This raises the urgent question of if and how groundwater can be used sustainably to provide sufficient water for crop production required to meet current and future food demands.

Here we will present the first results using a unique and novel modelling framework (i.e. VIC-Wageningen) that dynamically simulates the interactions between groundwater, surface water and crop growth worldwide. The new modelling framework is capable of estimating the direct and indirect contribution of groundwater to crop growth (i.e. through irrigation or through capillary rise supporting soil moisture,  respectively). VIC-Wageningen model is used to study current and future trade-offs between groundwater required for crop growth and groundwater required to support environmentally critical streamflow. Model results are evaluated against observations (e.g. groundwater heads and river discharge), with and without explicit simulation of groundwater processes. This model evaluation shows that the VIC-Wageningen model results in a more accurate estimate of groundwater availability for crop production and is useful to study the competition for groundwater between crop production and environmentally critical streamflow at the global scale. In addition, we are also exploring the added value of regional-scale studies, such as for the Indus River Basin, to improve model assessments at the global scale.
Performance of satellite rainfall estimates for flood and drought monitoring
Authors: Hamouda Mohamed , Hinge Gilbert , Mohamed Mohamed
Published: March 2022

In recent years, many researchers indicated that earth-observing satellites perform well in measuring or estimating precipitation rates. However, it has been highlighted that the performance of satellite rainfall estimates (SREs) is affected by many factors. In this study, a meta-data analysis was conducted to assess the performance of different SREs for flood and drought monitoring under diverse settings to test the influence of factors related to climate, topography, watershed size, and length of SREs data record. Koppen climate classification was used to classify the different studies into different climatic zone. Mean elevation was used as an indicator of varying topography. Studies were grouped into three different categories depending upon their available data record length. The impact of various factors on the performance of SREs was assessed with three statistical indices: Pearson correlation coefficient, Root Mean Square Error, and Nash-Sutcliffe Efficiency. Results showed that the performance of SREs for drought and flood monitoring is influenced by the climate, length of the data record, interactions between the applied hydrological model and type of SRE, and topography. Microwave-based SREs performed were found to perform better than infrared-based SREs. Low lying landscapes exhibited higher accuracy of SREs in flood and drought monitoring compared to complex mountainous terrain. In most cases, IMERG and CMORPH outperformed other SREs.  IMERG showed the best drought monitoring performance with Pearson correlation values ranging between 0.96-0.99. It was found that the best SREs that can represent the observed streamflow vary depending on the type of hydrological models. Also, the hydrological model performance for flood prediction significantly increases (p<0.05) when using the SREs for model calibration compared to when the model is manually calibrated with historical gauge data. Bias-adjusted SREs performed better than their counterpart. Overall, SREs offer great potential for flood and drought monitoring, but their performance needs to be enhanced for hydrological applications.