Multi-temporal Scale Research Articles

Spatio-temporal assessment of multi-scalar meteorological and hydrological droughts over Bundelkhand, India

Drought, a recurrent natural hazard, significantly impacts agricultural productivity, water resources, and socio-economic development, especially in semi-arid regions like Bundelkhand in India. Here, frequent droughts challenge the livelihoods of its predominantly agrarian population. These challenges, compounded by poverty, land degradation, and resource conflicts, have profound implications for local communities and the attainment of Sustainable Development Goals (SDGs). Understanding the spatiotemporal conditions of drought is crucial for effective planning and management. This study evaluates meteorological and hydrological drought attributes at a high resolution within the region, using the Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI) across a range of temporal scales. Findings indicate moderate droughts are more probable than severe or extreme droughts, with SPI-12 showing up to 20% probability over some grids, implying drought occurrence once in five years. Trend analysis reveals decreasing SPI trends in certain northern districts during monsoon months, suggesting more frequent droughts in vulnerable areas. The study also finds higher drought probabilities with longer SPI durations, highlighting significant temporal and spatial variability. Additionally, the applicability of SDI using GloFAS discharge data is evaluated, offering an alternative in the absence of gauge data. The combined SPI and SDI analysis underscores higher and more extensive drought probabilities for longer periods, emphasizing the need for multi-temporal scale assessment for effective drought management. This study enhances understanding of drought characteristics in the region, aiding policymaking for drought management and supporting evidence-based strategies to achieve SDGs, particularly those related to water security, climate resilience, and sustainable development.

Deciphering multi-temporal scale dynamics in the concentration, sources and processes of near surface ozone over different climatic regions of India.

This study aims to investigate the factors influencing seasonal and long-term (2003-2021) changes in the near surface ozone (850 hpa) concentrations over different climatic sub-regions of India. Detailed comparison of daily (2019-2021) near surface ozone values of ERA-5 and CAAQMS (Continuous Ambient Air Quality Monitoring Stations) ground-based measurements revealed that ERA-5 is temporally in phase with CAAQMS measurements falling indifferent climatic sub-regions of India. ERA-5 near surface ozone shows statistically significant long-term (2003-2021) positive trends [2-4 percent per decade (ppd)] over most of the climatic sub-regions, over Indo-Gangetic Planes (IGPs), Southern and Central India trends are particularly strong. Trends were also estimated for each season separately, which were largely positive (2-6 ppd) over Central and Southern India in the Autumn and Winter seasons. Extensive climatological analysis reveals that the reversal of winds in the Indian monsoonal system plays a vital role in such trend patterns across the Indian subcontinent. South-westerly winds from June through September presumably bring ozone deficit air of marine origin, thus causing a dilution effect while the North-easterly winds during late Autumn and early Winters plausibly bring ozone-rich air from the stratospheric-tropospheric efflux dominated Himalayan region. It allows near surface ozone enhancement over Central and Southern India. Seasonal Principal component analysis (PCA) revealed that precursor gases (CH4 and NO2) and climatic variables especially specific humidity (SH) are the primary drivers of near surface ozone variability in the Winter season, while in Spring, climatic variables like boundary layer height (BLH), temperature (T) and SH have a significant role. Principal component regression (PCR) reveals a long-term increase in near surface ozone levels mostly dominated by precursor concentration over IGPs and Southern sub-regions. Whereas, BLH, T and SH significantly explain near surface ozone trends over North-eastern and Coastal India.

Equalizing multi-temporal scale adequacy for low carbon power systems by co-planning short-term and seasonal energy storage

Power supply faces seasonal security risks due to the large seasonal volatility of renewable energy sources (RES) generation. Power systems with high shares of RES generation are more difficult to keep seasonal and daily/hourly supply adequacy at the same level. Therefore, this paper first addresses multi-temporal adequacy detail accounting for differences in RES output and timing of production, and demand. Then a planning approach is proposed for sizing short-term and seasonal energy storage accompanying with RES to achieve multi-temporal adequacy equilibrium. Unlike existing methods based on linking typical days or 8760-h simulations, the seasonal electricity adequacy constraints are captured by orderly clustering yearly net power curves, then the energy balance constraints are decoupled into long-term (i.e., seasonal) and short-term (i.e., hourly) energy balances. At the short-term scale, the robust optimization is used to address the uncertainty and randomness of wind and solar generation, in the same time realizing the coordination of short-term and seasonal energy storage. A modified column and constraint generation algorithm is used to solve the min-max-min model with binary variables. Finally, case studies are carried out on the Garver-6 system and the Northwest China Power Grid. The results demonstrate that the proposed planning method ensures multi-temporal scale adequacy equilibrium for high-RES power systems, and improving the planned system's economic performance.

Geospatial Insights into Aridity Conditions: MODIS Products and GIS Modeling in Northeast Brazil

Northeast Brazil (NEB), particularly its semiarid region, represents an area highly susceptible to the impacts of climate change, including severe droughts, and intense anthropogenic activities. These stresses may be accelerating environmental degradation and desertification of soil in NEB. The main aim of this study was to gain geospatial insights into the biophysical parameters of surface energy balance and actual evapotranspiration on a multi-temporal scale, aiming to detect and analyze the spectral behavioral patterns of areas vulnerable to degradation processes, based on thematic maps at the surface, for NEB and mainly the semiarid region of NEB from 2000 to 2019. Geospatial data from 8-day MODIS sensor products were used, such as surface reflectance (Terra/MOD09A1 and Aqua/MYD09A1), surface temperature (Terra/MOD11A2 and Aqua/MYD11A2), and actual evapotranspiration (Terra/MOD16A2 and Aqua/MYD16A2), version 6. Therefore, in this study, pixel-to-pixel values were processed by calculating the average pixel statistics for each year. From the reflectance product, digital processing of the surface albedo and spectral vegetation indices was also carried out, using computational programming scripts and machine learning algorithms developed via the Google Earth Engine (GEE) platform. The study also presents a seasonal analysis of these components and their relationships over 20 years. Through vegetation indices and statistical correlations, a new predictive model of actual evapotranspiration was developed. The quantitative and spatiotemporal spectral patterns of the parameters were assessed through descriptive statistics, measures of central tendency and dispersion, and statistical error analyses and correlation indices. Thematic maps highlighted the pixel-to-pixel results, with patterns of high temperature distribution mainly in the central and northeastern part of NEB and the semiarid region of NEB, highlighting the formation of persistent heat islands over time. Meanwhile, in these areas, the maps of actual evapotranspiration showed a drastic reduction due to the lesser availability of energy. Over time, the semiarid region of NEB presented areas with little and/or no vegetation cover, which were highly well-defined between the years 2012 and 2019, confirming that these areas are extremely vulnerable to degradation and desertification processes due to significant loss of vegetative and water resilience. The components of energy balance were highly interconnected to climatological and environmental conditions, showing the severe results of drought and accentuation of the water deficit in NEB, presenting a greater condition of aridity in the semiarid region of NEB over time.

Establishing a quantitative assessment methodology framework of water conservation based on the water balance method under spatiotemporal and different discontinuous ecosystem scales

Water conservation (WC) is an essential terrestrial ecosystem service that mitigates surface runoff and replenishes groundwater, which has received considerable attention under the dual pressures of climate change and human activity. However, there is insufficient understanding of the trends in WC changes on temporal (annual, monthly, daily), spatial, and ecosystem scales. This study proposed a quantitative assessment methodology framework (QAMF) for analyzing the spatiotemporal variation of WC under different discontinuous ecosystems. The QAMF mainly used models and methods such as the hydrological model (SWAT), calibration and uncertainty program (SWAT-CUP), WC calculation formula (water balance method), and spatial analysis method (empirical orthogonal function and wavelet analysis). It was applied to the source region of the Yellow River (SRYR), where the ecological landscape pattern underwent varying degrees of degradation, and WC capacity decreased. The results show that: Firstly, the constructed SWAT in the SRYR had high accuracy, and the proposed formula for calculating WC was suitable for multi-temporal scale analysis of WC in spatially distributed discontinuous basins. Secondly, the annual and monthly WC were respectively 81.00–184.13 mm and −28.58–107.64 mm, and daily WC was positive during extreme precipitation periods and negative during dry periods. The regulating effect of WC was fully reflected on the daily scale, partially reflected on the monthly scale, and absent on the annual scale. Third, the crucial WC area was mainly distributed in the southeast, and there was a significant primary yearly cycle of WC in the SRYR. Finally, different ecosystems exhibited different WC capabilities, and protecting the diversity of ecosystems played an essential role in maintaining and improving the WC function in the SRYR. This project has great scientific significance and technological support for scientifically evaluating the WC capacity in the SRYR.

Dynamics and biophysical controls of nocturnal water loss in a winter wheat-summer maize rotation cropland: a multi-temporal scale analysis

Nocturnal water loss (NWL), the evapotranspiration minus dew at night, has been identified to play a significant role in the surface water and energy balance. However, few studies have examined the variability in NWL in croplands with high water consumption across different timescales. Here, based on the eddy-covariance measurements of latent heat flux during nighttime, the dynamics and biophysical controls of NWL were examined in a winter wheat-summer maize rotation cropland in the North China Plain over a 5-year period (2008-2012) at nocturnal, seasonal and inter-annual scales. Besides, its relationship to drought was also revealed. Nocturnally, NWL showed a decreasing tendency from 20:00 to 05:00, with large diurnal variations in May. Seasonally, NWL was higher for wheat than that for maize. Interannually, the annual average daily NWL showed the same variation as the NWL during the wheat growth across the five years. The NWL was dominantly controlled by the difference between surface temperature and air temperature (Ts-Ta) nocturnally; Seasonally, NWL was influenced by vapor pressure deficit (VPD), wind speed (Ws) and site bulk surface conductance (gs) for wheat, and by VPD, gs and net radiation (Rn) for maize; NWL was mainly regulated by Ts-Ta and soil water content at 40 cm below the ground (VWC40) interannually. VPD and gs controlled NWL more during dry years. NDVI exhibited stronger control on NWL for wheat in wet years. The most favorable conditions for NWL during dry months were at Ta<16 ℃, VPD <0.8 kPa, and VWC40 <0.46 m3 m−3. NWL accounted for 4.0% of precipitation during the non-dry period but 19.6% during drought. Our results highlight the importance of biophysical factors in regulating NWL of the cropland ecosystem, and more attention should be paid to the influence of NWL on the water and carbon cycles in the context of climate change.

Attribution analysis of multi-temporal scale changes of streamflow in the source area of Lancang River with seasonal scale Budyko model

Under the influence of climate change and human activities, the intra-annual distribution characteristics of streamflow have changed, directly affecting the exploitation of water resources and the health of ecosystems. The trend-free pre-whitening Mann-Kendall (TFPW-MK) test method, concentration degree and concentration period, and Bernaola-Galvan (BG) segmentation algorithm were applied to analyze variation trend, intra-annual distribution characteristics, and abrupt year of streamflow. Then, the monthly water storage and monthly actual evaporation of the source area of the Lancang River (SALR) were calculated by the monthly ABCD model. Finally, the contributions of different factors to runoff variability at multiple time scales were quantified using the seasonal-scale Budyko hypothesis approach. The results showed that: (1) The runoff revealed a significant upward trend on the annual scale. Runoff exhibited a significant upward trend in January, October and November, and runoff in other months and seasons exhibited an insignificant upward trend. (2) The intra-annual distribution characteristics of runoff in the SALR showed an obvious “Single-peak type“ distribution, reaching a maximum in July and August. (3) The year of sudden change in streamflow was 2008. (4) The contribution of climate change and human activities to the annual runoff change was 83.3% and 16.7%, respectively. The degree of influence of climate change on runoff change was ranked as spring (96.8%), autumn (85.3%), winter (82.2%) and summer (58.2%). The order of impact of human activity on runoff change was summer (41.8%), winter (17.8%), autumn (14.7%), spring (3.2%).

Four-decade response of land surface temperature to urban expansion in Beijing

Urban expansion with increased impervious surface area (ISA) can affect the thermal regimes by altering the water and energy balance. Previous studies have indicated that ISA is the primary surrogate of rising land surface temperature (LST). However, urban-induced LST changes are not yet well quantified because of the temporal limitations of the LST datasets and the uncertainties from climate variabilities. In this study, we integrated multiple satellite-based products (vegetation coverage, albedo and radiation forcing) into a physically-based land surface model i.e., Variable Infiltration Capacity (VIC), to detect multi-temporal scale response of LST to the increasing ISA in Beijing. Heat transfer-related parameters in the model were updated along with urbanization processes. The integrated modeling presented high performance for simulating LST, as evaluated with ground-based observations and the MODerate-resolution Imaging Spectroradiometer (MODIS) LST product. We found that the average LST over Beijing increased from 10.3 °C in 1980–1990 to 11.2 °C in 2010–2020, with nearly 33% contributed by the urban growth. The urban-induced thermal effect was particularly strong in summer daytime and winter nighttime. The frequency of heat days (the day with the maximum LST over 40 °C) in a year for Beijing appeared to linearly correlate with the impervious surface fraction (ISF) when ISF > 25%. For the urbanizing area, moreover, the four-decade LST estimates indicated that the annual overheating duration was obviously extended with a rate of about 5 days per decade. We therefore conclude that the urban expansion in Beijing not only amplified heat stress but also altered heat phenology, which have implications for urban planning and the construction of heat mitigation facilities.

Extremes in water quality parameters modulated by weather and climate conditions in Ceara State, Brazil

Freshwater phytoplankton blooms are increasing in frequency worldwide and regularly put potable water resources, critical to human welfare, in jeopardy. Much more information is needed to effectively predict and mitigate these blooms. Prior studies have highlighted the roles played by both biological factors and physical ones (e.g., hydrodynamics, temperature, precipitation) in bloom formation. Most comprehensive studies have been limited to the temperate zone in Europe, China or North America; the dynamics of tropical and sub-tropical reservoirs are less well-characterised. Numerous studies have highlighted the relationship between phytoplankton and temperature or precipitation, but few have focused on the temporal scale of these relationships. This work evaluates the water quality of 155 freshwater reservoirs in Ceara state in northeast Brazil. We propose weather and climate conditions as natural drivers for changes in chlorophyll-a, cyanobacteria, total phosphorus and total nitrogen concentrations, that we consider as water quality parameters. We hypothesise that links between water quality and temperature and precipitation strongly depend on the timescale considered. Additionally, we propose a statistical definition, based on percentile thresholds, of extremes events in water quality, a criterion that has been lacking for the study of freshwater algal blooms and that will enable new regional and global comparisons. We aim to explore the potential links between extremes in water quality in tropical freshwater bodies of Ceara their predictors, by applying a multitemporal scale approach and discriminating the impact of the daily weather fluctuations from interannual climate variability. We find that water quality in Ceara is frequently below international standards, representing a threat for human and animal welfare. Reservoirs’ water level was a key predictor of bloom occurrence, thus linking low annual accumulated precipitation to inferior water quality. At the daily scale, high temperature promotes bloom formation during periods of drought. These findings suggest enhanced precautions during dry periods when the reservoirs are most prone to algal blooms, which can aggravate the drinking water scarcity in these years.

Appraisal of Climate Response to Vegetation Indices over Tropical Climate Region in India

Extreme climate events are becoming increasingly frequent and intense due to the global climate change. The present investigation aims to ascertain the nature of the climatic variables association with the vegetation variables such as Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI). In this study, the impact of climate change with respect to vegetation dynamics has been investigated over the Indian state of Haryana based on the monthly and yearly time-scale during the time period of 2010 to 2020. A time-series analysis of the climatic variables was carried out using the MODIS-derived NDVI and LAI datasets. The spatial mean for all the climatic variables except rainfall (taken sum for rainfall data to compute the accumulated rainfall) and vegetation parameters has been analyzed over the study area on monthly and yearly basis. The liaison of NDVI and LAI with the climatic variables were assessed at multi-temporal scale on the basis of Pearson correlation coefficients. The results obtained from the present investigation reveals that NDVI and LAI has strong significant relationship with climatic variables during the cropping months over study area. In contrast, during the non-cropping months, the relationship weakens but remains significant at the 0.05 significance level. Furthermore, the rainfall and relative humidity depict strong positive relationship with NDVI and LAI. On the other, negative trends were observed in case of other climatic variables due to the limitations of NDVI viz. saturation of values and lower sensitivity at higher LAI. The influence of aerosol optical depth was observed to be much higher on LAI as compared to NDVI. The present findings confirmed that the satellite-derived vegetation indices are significantly useful towards the advancement of knowledge about the association between climate variables and vegetation dynamics.

Effects of land use on multi-temporal scales of dissolved organic matter in Three Gorges Reservoir

Effects of land use on multi-temporal scales of dissolved organic matter in Three Gorges Reservoir

Where There's Smoke, There's Fuel: Dynamic Vegetation Data Improve Predictions of Wildfire Hazard in the Great Basin

Wildfires are a growing management concern in western US rangelands, where invasive annual grasses have altered fire regimes and contributed to an increased incidence of catastrophic large wildfires. Fire activity in arid, nonforested ecosystems is thought to be largely controlled by interannual variation in fuel amount, which in turn is controlled by antecedent weather. Thus, long-range forecasting of fire activity in rangelands should be feasible given annual estimates of fuel quantity. Using a 32-yr time series of spatial data, we employed machine learning algorithms to predict the relative probability of large (> 405 ha) wildfire in the Great Basin based on fine-scale annual and 16-d estimates of cover and production of vegetation functional groups, weather, and multitemporal scale drought indices. We evaluated the predictive utility of these models with a leave-1-yr-out cross-validation, building spatial hindcasts of fire probability for each year that we compared against actual footprints of large wildfires. Herbaceous aboveground biomass production, bare ground cover, and long-term drought indices were the most important predictors of burning. Across 32 fire seasons, 88% of the area burned in large wildfires coincided with the upper 3 deciles of predicted fire probabilities. At the scale of the Great Basin, several metrics of fire activity were moderately to strongly correlated with average fire probability, including total area burned in large wildfires, number of large wildfires, and maximum fire size. Our findings show that recent years of exceptional fire activity in the Great Basin were predictable based on antecedent weather-driven growth of fine fuels and reveal a significant increasing trend in fire probability over the past 3 decades driven by widespread changes in fine fuel characteristics.

The Spatiotemporal Characteristics of Flow-Sediment Relationships in a Hilly Watershed of the Chinese Loess Plateau.

The flow–sediment relationship is important to understand soil erosion and sediment transport in severely eroded areas, such as Loess Plateau. Previous research focused on the variation and driving forces of runoff and sediment at the different scales in a watershed. However, the variations of the flow–sediment relationship on multispatial scales (slope, subgully, gully, and watershed scales) and multitemporal scales (annual, flood events, and flood process) were less focused. Taking the Peijiamao watershed, which includes whole slope runoff plot (0.25 ha, slope scale), branch gully (6.9 ha, subgully scale), gully (45 ha, gully scale), and watershed (3930 ha, watershed scale), four different geomorphic units located at the Chinese Loess Plateau, as the research site, a total of 31 flood events from 1986 to 2008 were investigated, and two flood process data were recorded across all the four geomorphic units. The results showed that on the annual timescale, the average sediment transport modulus and runoff depth at four scales exhibited a linear relationship, with determination coefficients of 0.81, 0.72, 0.74, and 0.77, respectively. At the flood event timescale, the relationships between sediment transport modulus and runoff depth at the gully and watershed scales could also be fitted with a linear relationship with high determination coefficients (from 0.77 to 0.99), but the determination coefficient at the slope scale was only 0.37 at the event scale. On the single rainfall event timescale, the flow–sediment relationship at the slope scale showed a figure-eight hysteretic pattern while those relationships at larger scales showed an anticlockwise loop hysteretic pattern. Under the same flow condition, the suspended sediment concentrations during the falling stage were significantly higher than those during the rising stage. Moreover, the difference was bigger as the spatial scale increased due to the wash loads in the downstream gullies, which favored the occurrence of hyper-concentration flow. The results of the study could provide useful insights into the temporal–spatial scale effects of sediment transport and their internal driving mechanisms at the watershed scale.

Research on supporting mechanism of ancillary service of PV system to grid energy efficiency based on multi-time and space-time operation

Under the background of high-energy penetration of new energy into the power grid, this paper takes the ancillary service capability of photovoltaic energy integrated into the grid as the starting point and builds a photovoltaic system reactive power service impact evaluation model on the grid energy efficiency. This is based on the multi-temporal and spatial scale operation mode, in order to study the supporting principles of photovoltaic system reactive power services on the energy efficiency of grid operation and the law of influence on system energy efficiency changes. In this way, the space for power system energy efficiency improvement and the reactive power service market value of renewable energy are explored to improve the renewable energy auxiliary services participation in the theoretical system of electric power spot market transactions. The research conclusions can provide a decision-making reference for system dynamic energy efficiency management and can assist relevant market entities to make optimal decisions in spot market transactions, and provide empirical data for improving the theory of renewable energy participation in auxiliary service market transactions.

Impact of BRDF Spatiotemporal Smoothing on Land Surface Albedo Estimation

Surface albedo, as a key parameter determining the partition of solar radiation at the Earth’s surface, has been developed into a satellite-based product from various Earth observation systems to serve numerous global or regional applications. Studies point out that apparent uncertainty can be introduced into albedo retrieval without consideration of surface anisotropy, which is a challenge to albedo estimation especially from observations with fewer angular samplings. Researchers have begun to introduce smoothed anisotropy prior knowledge into albedo estimation to improve the inversion efficiency, or for the scenario of observations with signal or poor angular sampling. Thus, it is necessary to further understand the potential influence of smoothed anisotropy features adopted in albedo estimation. We investigated the albedo variation induced by BRDF smoothing at both temporal and spatial scales over six typical landscapes in North America using MODIS standard anisotropy products with high quality BRDF inversed from multi-angle observations in 500 m and 5.6 km spatial resolutions. Components of selected typical landscapes were assessed with the confidence of the MCD12 land cover product and 30 m CDL (cropland data layer) classification maps followed by an evaluation of spatial heterogeneity in 30 m scale through the semi-variogram model. High quality BRDF of MODIS standard anisotropy products were smoothed in multi-temporal scales of 8 days, 16 days, and 32 days, and in multi-spatial scales from 500 m to 5.6 km. The induced relative and absolute albedo differences were estimated using the RossThick-LiSparseR model and BRDFs smoothed before and after spatiotemporal smoothing. Our results show that albedo estimated using BRDFs smoothed temporally from daily to monthly over each scenario exhibits relative differences of 11.3%, 12.5%, and 27.2% and detectable absolute differences of 0.025, 0.012, and 0.013, respectively, in MODIS near-infrared (0.7–5.0 µm), short-wave (0.3–5.0 µm), and visible (0.3–0.7 µm) broad bands. When BRDFs of investigated landscapes are smoothed from 500 m to 5.6 km, variations of estimated albedo can achieve up to 36.5%, 37.1%, and 94.7% on relative difference and absolute difference of 0.037, 0.024, and 0.018, respectively, in near-infrared (0.7–5.0 µm), short wave (0.3–5.0 µm), and visible (0.3–0.7 µm) broad bands. In addition, albedo differences caused by temporal smoothing show apparent seasonal characteristic that the differences are significantly higher in spring and summer than those in autumn and winter, while albedo differences induced by spatial smoothing exhibit a noticeable relationship with sill values of a fitted semi-variogram marked by a correlation coefficient of 0.8876. Both relative and absolute albedo differences induced by BRDF smoothing are demonstrated to be captured, thus, it is necessary to avoid the smoothing process in quantitative remote sensing communities, especially when immediate anisotropy retrievals are available at the required spatiotemporal scale.

Ice Dynamics and Morphological Changes During Proglacial Lake Development at Exploradores Glacier, Patagonia

Proglacial lakes are ubiquitous features formed during deglaciarization and are currently increasing in number in Patagonia and elsewhere. Proglacial lakes can affect glacier dynamics, catchment hydrology and have the potential to cause glacial lake outburst floods. Therefore, monitoring the onset and development of proglacial lake formation is relevant to understand glacial processes and anticipate glacier response to climate change. In this study, we integrate geomorphological and ice-dynamic information to assess proglacial lake development in Exploradores Glacier, Chilean Patagonia. We monitor recent spatial and temporal changes in the lower trunk of Exploradores Glacier (10 km2) to provide a 20-year observation record by combining eight uncrewed aerial vehicles (UAV) surveys between 2019 and 2020, with high-medium resolution satellite imagery (Rapid Eye and Landsat) between 2000 and 2018. We use feature tracking techniques, digital surface elevation model analysis and field data to create a multi-temporal scale (inter-annual and seasonal) and a multi-spatial (cm to km) data set. Our analysis shows that surface velocity overall trend has not changed over the last 20 years and that surface velocity near the terminus is significant (&amp;gt;10 m a−1). Moreover, an exceptional advance over moraine deposits was detected. We also found low downwasting rates (&amp;lt;0.5 m a−1) close to the glacier terminus which are attributed to sufficient ice flux and the insulation effect of the debris-covered surface. However, hundreds of supraglacial ponds were observed and are currently coalescing and expanding by ice-cliff backwasting favoring glacier disintegration. Lastly, it was found that calving losses at the east marginal lake equaled ice-flux input into the lake for the UAV monitored period. This study contributes to a better understanding of glacial lake dynamics during proglacial lake development, and our results may help ice modelling efforts to predict glacier response to future climate scenarios.

Revisiting the cumulative effects of drought on global gross primary productivity based on new long-term series data (1982-2018).

Drought has broad and deep impacts on vegetation. Studies on the effects of drought on vegetation have been conducted over years. Recently, the cumulative effect of drought is recognized as another key factor affecting plant growth. However, global-scale studies on this phenomenon are still lacking. Thus, based on new satellite based gross primary productivity (GPP) and multi-temporal scale Standardized Precipitation Evapotranspiration Index data sets, we explored the cumulative effect duration (CED) of drought on global vegetation GPP and analyzed its variability across elevations and climatic zones. The main findings were as follows: (1) The cumulative effect of drought on GPP was widespread, with an average CED of 4.89months. (2) CED of drought on GPP varied among vegetation types. Specifically, grasslands showed the longest duration, with an average value of 5.28months, followed by shrublands (5.09months), wetlands (5.03months), croplands (4.85months), savannas (4.58months), and forestlands (4.57months). (3) CED of drought on GPP changes with climate conditions. It decreased with the decrease of precipitation in the driest month (Pdry ) and mean annual precipitation in tropical and arid climate zones, respectively. In both temperate and cold climate zones, CED of drought on GPP was shorter in areas with dry winter than that in areas with dry summer. It increased with the decrease of mean annual air temperature in tropical climate zones and decreased with the increase of summer temperature in temperate and cold climatic zones. (4) With increasing elevation, CED of drought on GPP showed a pattern of increasing (0-3000m), then decreasing (3000-5000m), and increasing again (>5000m). Our findings highlight the heterogeneity of CED of drought on GPP, owing to differences in vegetation types, long-term hydrothermal conditions, elevation, etc. The results could deepen our understanding of the effects of drought on global vegetation.

Hydrological effects of large dams in Chilean rivers

Study regionEight rivers regulated by large dams located in three hydro-climatic zones along the Chilean latitudinal gradient. Study focusWe performed a multi-temporal scale analysis of flow records and we used data from official gauging stations to characterise the non-altered and the altered river regimes to determine the magnitude and persistence of the hydrological alteration downstream from large dams in Chile. These analyses provide relevant information to improve the understanding of such alterations, and a conceptual basis for assessing future impacts as the country plans to build a series of large dams in the coming years. New hydrological insights for the regionThe mean annual runoff was reduced in all the study rivers. The monthly flows of the rivers from the northern arid zone were the most affected by the dams. The magnitude and frequency of floods decreased in all the study rivers. Moreover, northern drier river systems did not recover their hydrological conditions in the distance downstream of the dams, probably due to transmission losses and water extractions and diversions; in contrast, southern rivers partially recovered their flow regimes with distance downstream, mainly due to the inflows from permanent non-regulated tributaries. So far, this is the first study in Chile that comprehensively analyses the hydrological effects of large dams.

Effects of multi-temporal scale drought on vegetation dynamics in Inner Mongolia from 1982 to 2015, China

Climate change is causing severe changes in the ecosystem, thus understanding how plants respond to drought is essential to protecting ecosystems in Inner Mongolia. Multi-temporal variations of drought in Inner Mongolia were studied using the Standardized Precipitation Evapotranspiration Index (SPEI), and the vegetation growth was analyzed using the Normalized Difference Vegetation Index (NDVI). Moreover, the correlation between droughts of different lengths and NDVI was studied. Subsequently, we developed an optimal binary probability model to calculate the probability of vegetation productivity loss at different drought levels using the copula method. The results showed: (1) a weak aridification in the western parts and significant wetness in the central and eastern parts of Inner Mongolia; (2) a significant decreasing trend of NDVI from 1982 to 2009 and a significant increasing trend from 2010 to 2015; (3) a strong positive correlation between NDVI and SPEI and a difference between their related time scales based on soil textures; and (4) a higher probability of vegetation productivity loss with increasing drought at different drought levels.

Exploring the Spatio-Temporal Variability of Precipitation over the Medjerda Transboundary Basin in North Africa

Medjerda is a key transboundary watershed in the Maghreb region, crossing from the Algerian mountains through northern Tunisia. Therefore, the analysis of the rainfall regime in this basin is of paramount importance for water resources management and regional economic development, notably concerning agriculture. This study examines the rainfall trends over the Medjerda watershed on multi-temporal scales (monthly, seasonally and annually) with a database of monthly rainfall observed in 60 stations evenly spread over the watershed. After filling gaps and homogenizing data, the Mann–Kendall test for trend detection was applied to rainfall series and the Sen’s slope method was adopted to estimate the trend’s magnitude, interpolated over the sub-catchments, to analyze the spatial distribution of rainfall changes within the watershed. Results showed the absence of significant trends at the annual scale for the entire catchment. However, rainfall redistribution was observed throughout the year, with a notable precipitation reduction during spring and increased winter precipitation, which could impact agriculture and ecosystem functioning. This modification of the rainfall regime implies an adaptation of the management of dams and reservoirs, with a reduced filling capacity during spring in anticipation of the summer dry season.