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Since 1990, global forest area has been reducing; tropical forests have suffered from different anthropogenic and natural factors that account for forest loss. Tropical deforestation is the second driver of anthropogenic emissions; increasing demand and investments in tropical forests drive these emissions. These forests attract significant foreign direct investments, but the effects of these investments on carbon emissions from land use, land-use change, and forestry are not well enshrined in the literature for the countries under study. This paper seeks to analyse the impact of foreign direct investments on carbon emissions from land use, land-use change, and forestry amongst 30 tropical forest countries from 1996 to 2019. The sampled countries were disaggregated by tropical blocs: Amazon, Congo basin, Australasia, and Southeast Asia, and by income levels; low-income, lower-middle, upper-middle, and high-income. The findings reveal a U-shape structure of the impact of FDI on carbon emissions from LULUCF within Congo basin and Amazon countries; at higher levels of FDI, emissions from LULUCF will increase while Australasia and Southeast Asian countries show an inverted U-shape impact, thus at higher levels of FDI, there will be a negative and significant impact on carbon emissions from LULUCF. The income levels reveal an inverted U-shape for low-income and high-income countries and a U-shape for upper-middle-income countries; the impact for lower-middle-income countries is not significant. Overall, for the whole sample, the impact depicts a U-shape. This paper proposes high-level development of environmental conditions for FDI for different sectors that align with country and regional green growth plans. Enhancing national and regional governance systems to enforce decisions and fight corruption effectively can significantly promote green FDI for green growth. [ABSTRACT FROM AUTHOR]

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There have been several incidences of flood recently, which are believed to be aggravated by increased climatic variables as a result of perceived changes in climatic conditions (due to climate change) in the Cross River Basin. The basin is the most extensively developed and used river basin in the management of the water resources of the Cross River and Akwa Ibom States in Nigeria. In this paper, 30 years (from 1992 to 2021) of hydro-meteorological data (annual average rainfall, maximum and minimum temperatures, hu midity, duration of sunlight (sunshine hours), evaporation, wind speed, soil temperature, cloud cover, solar radiation, and atmospheric pressure) from four stations in the Cross River Basin were obtained from the Nigerian Meteorological Agency (NIMET), Abuja and subjected to trend detection analysis using the Mann–Kendall test to determine the trend in climatic parameters. The results indicate that there is a significant upward trend in annual rainfall in Ogoja but a downward trend in Calabar. The evaporation trend is significantly downward in Eket, whereas in Calabar, there is an upward trend in solar radiation. Generally, there is a significant rise in annual maximum temperature across the basin. Serial correlation and segmented regression analyses were performed to measure the impact of fluctuations in monthly and long-term Tahiti and Darwin's Sea level pressures on the climatic variables at the Cross River Basin catchment. These analyses were necessary to determine the extent of the influence of the El Nino Southern Oscillation climatic cycle. The analyses show no significant association between the El Niño Southern Oscillation (ENSO) and rainfall or between the ENSO and runoff in the catchment. This implies that the impact of the ENSO on rainfall and runoff in the Cross River Basin catchment is not considerable. The intercepts derived from the segmented regression in Eket and Ogoja show significant positive trends in both areas for rainfall and runoff. The trends in intercepts suggest that there are external factors influencing rainfall and runoff other than ENSO events, thus strengthening the assertion of climate change. Results from this study will facilitate the understanding of the variability in climatic parameters by stakeholders in the basin, researchers, policymakers, and water resource managers. [ABSTRACT FROM AUTHOR]

This paper presents a method to analyze and improve the set of equations constituting a rainfall‐runoff model structure based on a combination of a data assimilation algorithm and polynomial updates to the state equations. The method, which we have called "Data Assimilation Informed model Structure Improvement" (DAISI) is generic, modular, and demonstrated with an application to the GR2M model and 201 catchments in South‐East Australia. Our results show that the updated model generated with DAISI generally performed better for all metrics considered included Kling‐Gupta Efficiency, NSE on log transform flow and flow duration curve bias. In addition, the elasticity of modeled runoff to rainfall is higher in the updated model, which suggests that the structural changes could have a significant impact on climate change simulations. Finally, the DAISI diagnostic identified a reduced number of update configurations in the GR2M structure with distinct regional patterns in three sub‐regions of the modeling domain (Western Victoria, central region, and Northern New South Wales). These configurations correspond to specific polynomials of the state variables that could be used to improve equations in a revised model. Several potential improvements of DAISI are proposed including the use of additional observed variables such as actual evapotranspiration to better constrain internal model fluxes. Plain Language Summary: This paper presents a data‐driven method to improve rainfall‐runoff models used to generate future water resources scenario in climate change studies. The method, which we have called "Data Assimilation Informed model Structure Improvement" (DAISI) is generic, modular, and demonstrated with an application to monthly streamflow simulations over a large data set of catchments in South‐East Australia. Our results show that DAISI improves model performance for a wide range of metrics and increases the sensitivity of the model to climate inputs, which is critical in climate change scenarios. Finally, the improvements identified by DAISI take a simple mathematical form with distinct regional patterns in three sub‐regions of the study domain (Western Victoria, central region, and Northern New South Wales). Several improvements of DAISI are discussed including the inclusion of additional observed variables such as evapotranspiration to better constrain model simulations. Key Points: Data Assimilation Informed model Structure Improvement method diagnoses hydrological model structures by combining data assimilation with a polynomial update of state equationsThe method was applied to the GR2M rainfall‐runoff model with significantly improved streamflow simulations in 201 Australian catchmentsThe method identified updates to state equations with marked regional characteristics that could guide future improvement of GR2M [ABSTRACT FROM AUTHOR]

Wildfires pose one of the greatest threats to the world's forests soils. After exposure to fire, forests lose many of their ecological functions; moreover, the repercussions can extend well beyond the forest itself, as the erosive processes attributable to the combustion of vegetation and the soil's lack of protection against rainfall are likely to impact any areas of a catchment, contaminating reservoirs, estuaries and aquifers. A forest fire is not solely, therefore, an environmental issue, but also a social and economic problem. The recovery of a forest is heavily dependent on just how the soil has been affected and how rapidly the latter can be restored. Fire intensity is critical in understanding the temporal evolution of the forest, while its location--a clear determinant of its climate and the ecosystem it occupies--can undermine the functionality of the forest system and is critical in determining the duration of the effects of the fire episode. This paper undertakes a review of the literature with the aim of understanding what might be understood when studies speak of the long-term effects of fire on the soil and when a soil might be considered to have recovered from these effects. What is evident is that many variables have a role to play and that not all soil properties recover at the same rate; indeed, some may never be restored to pre-fire levels. [ABSTRACT FROM AUTHOR]

The response of dryland vegetation to climate change is particularly sensitive in the context of global climate change. This paper analyzes the characteristics of spatial and temporal dynamics of vegetation cover in the Tarim River Basin, China, and its driving factors in order to investigate the response of vegetation growth to water storage changes in the basin. The Enhanced Vegetation Index (EVI), the GRACE gravity satellite, and meteorological data from 2002 to 2022 are used to decipher the characteristics of the response of water storage changes to vegetation changes, which is of great significance to the realization of regional ecological development and sustainable development. The results of the study show the following: (1) The vegetation in the Tarim River Basin has an overall increasing trend, which is mainly distributed in the Aksu Basin and the Weigangkuche River Basin and is spatially distributed in the form of a ring. (2) Vegetation distribution greatly improved during the 20-year study period, dominated by high-cover vegetation, with a change rate of 200.36%. Additionally, vegetation changes are centered on the watersheds and expand to the surrounding area, with a clear increase in vegetation in the Kumukuri Basin. Areas with a vegetation Hurst index of <0.5 account for 63.27% of the study area, and the areas with a continuous decrease were mainly located in the outer contour area of the Tarim River and Kumu Kuri Basins. (3) There are obvious spatial differences in the correlation between EVI and temperature and precipitation elements. The proportion of areas with positive correlation with temperature within the study area is 64.67%. EVI tends to be consistent with the direction of migration of the center of gravity of the population and GDP, and the areas with positive correlation between vegetation and terrestrial water reserves are mainly distributed in the northern slopes of the Kunlun Mountains, with an area proportion of about 50.513%. The Kumukuli Basin also shows significantly positive correlation. [ABSTRACT FROM AUTHOR]

The Pearl River is one of China's large rivers, the second-largest river and the fourth-longest river in China. Its unique geography, landform, and climate conditions create unique fluvial geomorphological processes. Affected by human activities and climate change, the fluvial geomorphological processes in the Pearl River Basin have undergone significant changes in recent decades, seriously affecting the river's sustainable development. This paper critically reviews changes in fluvial geomorphological processes and analyzes influencing factors in the Pearl River Basin with a focus on possibilities for policy overhaul and strategic adjustments. [ABSTRACT FROM AUTHOR]

Climate change and human activities exert significant influence on the water–sediment relationship in arid and semi-arid regions. Therefore, comprehending the underlying mechanisms is crucial for the effective management of water and soil resources, as well as integrated watershed management. This research focuses on the Kuye River watershed (KYH_W) in the middle reaches of the Yellow River in China, along with its sub-watersheds Wangdaohengtazi (WDHT_SW) and Xinmiaosi (XM_SW). This paper utilizes the Mann–Kendall non-parametric test and the double cumulative curve method to examine the interannual trends of runoff, sediment transport, precipitation, temperature, and NDVI factors. Furthermore, the method of the slope change ratio of cumulative quantity (SCRCQ) is utilized to quantitatively evaluate the impacts and contribution rates of climate change and human activities on water–sediment changes within each watershed. The results are as follows: (1) From 1969 to 2019, the entire watershed experienced a significant decrease in both runoff and sediment transport, with 1997 marking the year of abrupt change. However, following 2012, the KYH_W and WDHT_SW exhibited a noticeable rebound in runoff. (2) Human activities predominantly contribute to the reduction in water and sediment in the watershed. (3) After the abrupt change, between 1998 and 2011, the contribution rates of climate change and human activities to the annual runoff reduction in the entire KYH_W reached 33% and 64%, respectively. Moreover, these rates for sediment transport reduction reached 26% and 74%, respectively. Subsequently, after 2012, the contribution rates of both factors to the increase in watershed runoff reached 29% and 71%, respectively. Factors other than the NDVI, within human activities, played a dominant role in augmenting the watershed's runoff. (4) Prior to 2011, changes in vegetation cover resulting from the Grain for Green Program, as measured by the NDVI, emerged as the primary factor responsible for reduced runoff in the watershed. Conversely, factors other than the NDVI assumed dominance in reducing sediment transport. The SCRCQ method offers a quantitative approach to assessing water–sediment changes. Based on this method, the study further underscores the substantial impacts of climate change and human activities on variations in runoff and sediment transport within the KYH_W in the middle reaches of the Yellow River. Notably, the water–sediment changes in the KYH_W exhibit distinct stage-wise and spatial discrepancies, which warrant increased attention in future research endeavors. [ABSTRACT FROM AUTHOR]

Arid zone ecosystems, integral to terrestrial systems, exhibit relatively low stability and are prone to influences from human activities and climate change. To elucidate the influence on the ecological environment of the arid zone by climate change and human activities, the paper takes normalized difference vegetation index (NDVI) as an evaluation index of the ecosystem and uses trend analysis to evaluation of NDVI variation characteristics in the Shiyang River Basin (SRB) from 1990 to 2020. Simultaneously using methods such as partial correlation analysis and residual analysis to evaluate the impact of climate change and human activities on NDVI changes. This study yielded several key findings: (1) The NDVI in the SRB exhibits an increasing trend of 0.034/10a in the interannual variation. (2) The relation cooperatives between NDVI and the deviation of precipitation and temperature in the SRB range from −0.735 to 0.770 and −0.602 to 0.773, respectively. (3) The changes in land use and groundwater depth in the SRB have a certain impact on NDVI changes. (4) The proportion of areas with significant contributions (contribution rate greater than 60%) from climate change and human activities to NDVI change is 33.5% and 22.5%, respectively. [ABSTRACT FROM AUTHOR]

Accurate assessment of water resources at the watershed level is crucial for effective integrated watershed management. While semi-distributed/distributed models require complex structures and large amounts of input data, conceptual models have gained attention as an alternative to watershed modeling. In this paper, the performance of the GR4J conceptual model for runoff simulation in the Gambia watershed at Simenti station is analyzed over the calibration (1981–1990) and validation period (1991–2000 and 2001–2010). The main inputs to conceptual models like GR4J are daily precipitation data and potential evapotranspiration (PET) measured from the same catchment or a nearby location. Calibration of these models is typically performed using the Nash–Sutcliffe daily efficiency with a bias penalty as the objective function. In this case, the GR4J model is calibrated using four optimization parameters. To evaluate the effectiveness of the model's runoff predictions, various statistical measures such as Nash–Sutcliffe efficiency, coefficient of determination, bias, and linear correlation coefficient are calculated. The results obtained in the Gambia watershed at Simenti station indicate satisfactory performance of the GR4J model in terms of forecast accuracy and computational efficiency. The Nash–Sutcliffe (Q) values are 0.623 and 0.711 during the calibration period (1981–1990) and the validation period (1991–2000), respectively. The average annual flow observed during the calibration period is 0.385 mm while it increases with a value of 0.603 mm during the validation period. As for the average flow simulated by the model, it is 0.142 mm during the calibration period (i.e., a delay of 0.142 mm compared to the observed flow), 0.626 mm in the validation period (i.e., an excess of 0.023 mm compared to the observed flow). However, this study is significant because it shows significant changes in all metrics in the watershed sample under different scenarios, especially the SSP245 and SSP585 scenarios over the period 2021–2100. These changes suggest a downward trend in flows, which would pose significant challenges for water management. Therefore, it is clear that sustainable water management would require substantial adaptation measures to cope with these changes. [ABSTRACT FROM AUTHOR]

Xinjiang, located in the arid region of the northwest, is one of the areas most sensitive to global changes. The Kaidu River Basin, situated in the heart of Xinjiang, is one of the sources of China's largest inland river—the Tarim River. The Kaidu River not only bears the responsibility for supplying water for industrial use and agricultural production and people's daily life in the basin, but also plays a crucial role in ecological water supply to the Tarim River. Studying and analyzing the characteristics and trends of meteorological condition in the future under climate change can provide important references and a basis for a deeper understanding of changes in the hydrological process and water resources in the basin. Therefore, this paper selects seven precipitation bias correction methods and four temperature bias correction methods to adjust the precipitation and temperature output data of eight general circulation models of the Sixth Coupled Model Intercomparison Project (CMIP6) within the Kaidu River Basin. The applicability of different bias correction methods in the study area is evaluated, and based on the corrected future meteorological data and calculated extreme meteorological index, the trends of meteorological data (precipitation, temperature) in the future period (2025–2050) under four SSP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) in the Kaidu River Basin are analyzed. The results show that: (1) Different types of bias correction methods have different correction focus and effects; their reflections on evaluation indicators are also different. (2) In the future period (2025–2050), the annual precipitation and average temperature in the Kaidu River Basin are higher than those in the historical period (1975–2014). The average annual temperature shows an upward trend in the future, but the annual precipitation shows a downward trend in the future except for the SSP2-4.5 scenario. (3) Compared with the historical period, the extreme precipitation in the future period under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios is higher than that in the historical period, and the number of rainless days decreases. In the future, under the SSP1-2.6 and SSP5-8.5 scenarios, the probability of meteorological drought events occurring due to high temperatures in the basin may further increase, while under the SSP2-4.5 scenario, the situation of high temperatures and heavy rain in the basin may continue to increase. [ABSTRACT FROM AUTHOR]

This paper presents a hydrological assessment of the 113,981 km2 Meta River basin in Colombia using 13 global climate models to predict water yield for 2050 under two CMIP6 scenarios, SSP 4.5 and SSP 8.5. Despite mixed performance across subbasins, the model was notably effective in the upper Meta River subbasin. This study predicts an overall increase in the basin's annual water yield due to increased precipitation, especially in flatter regions. Under the SSP 4.5, the Meta River basin's water flow is expected to rise from 5141.6 m3/s to 6397.5 m3/s, and to 6101.5 m3/s under the SSP 8.5 scenario, marking 24% and 19% increases in water yield, respectively. Conversely, the upper Meta River subbasin may experience a slight decrease in water yield, while the upper Casanare River subbasin is predicted to see significant increases. The South Cravo River subbasin, however, is expected to face a considerable decline in water yield, indicating potential water scarcity. This study represents a pioneering large-scale application of the InVEST–AWY model in Colombia using CMIP6 global climate models with an integrated approach to produce predictions of future water yields. [ABSTRACT FROM AUTHOR]

Global climate change has affected vegetation cover in alpine areas. In this paper, we analyzed the correlation between Leaf Area Index (LAI) and climate factors of the Yarlung Tsangpo River basin, and identified their contributions using the quantitative analysis method. The results show that the vegetation cover in the study area generally exhibited an increasing trend. Grassland in the middle- and high-altitude areas was the main contributing area. Temperature is the dominant climatic factor affecting the change, the effect of which increases with the rise in elevation. The influences of precipitation and radiation had obvious seasonality and regionality. The vegetation illustrated a lag response to climate drivers. With the change in the elevation band, the response time to precipitation was significantly less than that to air temperature in the low-elevation area, while the opposite trend was observed in the high-elevation area. In the future, the LAI of the watershed will show different characteristics at different time points, with the increases in the LAI in autumn and winter becoming the main factors for the future increase in the LAI. This provides a crucial basis upon which to explore hydrological and ecological processes as important components of the Third Pole region. [ABSTRACT FROM AUTHOR]

Harmful algae and cyanobacteria blooms are increasing in frequency and intensity in freshwater systems due to anthropogenic impacts such as nutrient loading in watersheds and engineered alterations of natural waterways. There are multiple physical factors that affect the conditions in a freshwater system that contribute to optimal habitats for harmful algae and toxin-producing cyanobacteria. A growing body of research shows that climate change stressors also are impacting water-body conditions that favor harmful algae and cyanobacteria species over other phytoplankton. The overgrowth of these organisms, or a "bloom," increases the opportunity for exposure to toxins by humans, companion animals, livestock, and wildlife. As waters warm and precipitation patterns change over time, exposure to these blooms is projected to increase. Hence, it is important that states and tribes develop monitoring and reporting strategies as well as align governmental policies to protect their citizens and ecosystems within their jurisdiction. Currently, the policies and approaches taken to monitor and report on harmful algae and cyanobacteria blooms vary widely among states, and it is undetermined if any tribes have specific policies on harmful algae blooms. This paper synthesizes research on algal blooms in inland freshwater systems of the United States. This review examines how climate change contributes to trends in bloom frequency or severity and outlines approaches that states and tribes may use to monitor, report, and respond to harmful algae and cyanobacteria blooms. Significance Statement: Inland bodies of freshwater supply drinking water for humans and animals, water for irrigating crops, habitats for aquatic species, places of cultural significance for Indigenous peoples, and other important functions. Many of these bodies of water have been polluted with runoff from industry, including agriculture, and already support harmful algal blooms during warm conditions. Hot extremes associated with climate change are expected to increase the occurrence and duration of harmful algal blooms, and in some places, initiate blooms where none have been recorded previously. These toxic blooms are harmful to people, companion animals, livestock, and wildlife. It is important to review the interconnections among biological, climate, and water systems to monitor blooms and alert the public about their toxin production. [ABSTRACT FROM AUTHOR]

Sub-Saharan Africa, of which Kenya is part, is considered the most vulnerable region to climate change impacts due to its dependence on rain-fed agriculture and natural resources. Since the rural livelihood systems in Kenya are expected to bear some of the worst effects of climate change, it is imperative to assess rural households' vulnerability to climate change impacts to facilitate the development of adaptation strategies. Therefore, this paper determines the level and sources of households' livelihood vulnerability to climate variability in the Migori River watershed, Kenya. The Livelihood Vulnerability Index (LVI) framed within the Intergovernmental Panel on Climate Change (IPCC) vulnerability framework (LVI-IPCC) was applied. A cross-sectional household survey conducted on 318 randomly selected households was used to assess how vulnerability differs across three watershed zones, upstream, midstream, and downstream. The LVI-IPCC scores were −0.047, −0.003, and 0.008 for the upstream, midstream, and downstream zones, respectively, with significant differences noted in the scores (ANOVA, p < 0.05). Findings indicate that while the livelihoods in all three zones showed moderate vulnerability to environmental and socio-economic stressors, there are notable variations between them. The downstream households exhibit the highest vulnerability, attributed to their lower adaptive capacity, increased exposure, and heightened sensitivity. Conversely, the upstream households demonstrate the least vulnerability compared to the other zones, owing to their lower sensitivity and exposure, as well as better adaptive capacity. Policy recommendations for reducing households' exposure to climate risks and for strengthening their adaptive capacity are discussed. [ABSTRACT FROM AUTHOR]

Currently, climate change is considered as an important factor affecting nutrient loads introduced through riverine systems into the Baltic Sea. Although the prospect of a large increase in pollution has long seemed very real, it still does not translate into planning of effective remedial actions. One of the factors limiting the development of such activities is the scale of simulations, focusing generally on catchment outlet profiles. To fill this gap and enable a step forward in understanding responses toward future predictions in a higher resolution scale (subcatchment), we assessed nutrient load contribution using calculation profiles localized along a main watercourse and its tributaries. To track spatial and seasonal changes of total nitrogen and phosphorus for the Wełna River (central Poland), we used climate change data and the SWAT model. Having at our disposal a catchment model with a good performance we could follow not only total load changes in particular subcatchments, but also track localization of the pollution sources and their direct impact on load estimations. Our results showed an increase of the loads, especially from the agricultural land use type, up to 34% for TN and 85% for TP, in the most extreme scenario. Moreover, forest areas have been noted as highly reactive to climate change, and through their localisation are able to distinctly alter nutrient outflow. Finally, the contribution of urban areas should be further investigated since the dynamics of nitrogen and phosphorus release from impervious surfaces is noticeably different here than from the other diffuse sources. Plain Language Summary: This paper describes how climate change will affect the amount of nutrients in a small river catchment in the Baltic Sea region. While it is known that climate change can increase nutrient loads, effective actions to prevent them are still lacking. The "big picture" based on a whole catchment is still poor in terms of finding nutrient vulnerable areas. In this research, we looked at a more detailed scale to see where the nutrients are coming from and how they are changing over time. We used computer modeling to show that the amount of nutrients coming from agriculture, forests, and city areas will increase due to climate change. Overall, the amount of nitrogen can raise by 34% and the amount of phosphorus by 85%. Our results can be the basis for making decisions regarding actions aimed at improving the condition of surface waters and counteracting climate change effects. Key Points: Spatio‐temporal trends of nutrient loads have been tracked in a Baltic Sea region catchment under climate change scenariosClimate change suggests a potential load increase from the whole catchment by 34% for total nitrogen and 85% for total phosphorusOutputs from individual nutrient sources could grow by even 187% for total nitrogen and 302% for total phosphorus [ABSTRACT FROM AUTHOR]

In the past decades, land use pattern and climate conditions of Shaying River Basin have changed significantly, which will inevitably have a significant impact on the river hydrological situation. Therefore, in order to study the response of the hydrological cycle process of the Shaying River Basin to land use and climate changes, this paper constructed the Soil and Water Assessment Tool (SWAT) hydrological model of the Shaying River Basin based on historical meteorological and hydrological data, and conducted parameter calibration and model verification to quantitatively explore the response of the runoff of the Shaying River Basin to different land use and climate change scenarios. The results showed that: (1) In calibration and verification periods, the determination coefficients (R2) were 0.80 and 0.83 respectively, the Nash–Sutcliffe efficiency coefficients (NSE) were 0.77 and 0.73 respectively, and the percentage deviation (PBIAS) was within ± 25%. (2) Setting different combinations of land use and climate changes into four scenarios S1, S2, S3, and S4, the simulated runoff depths were 257 mm, 298 mm, 259 mm, and 301 mm, respectively. The impacts of land use and climate changes on the annual runoff of Shaying River were 0.9% and 16.1% respectively. (3) In the scenario with 4 °C reduction and 20% precipitation increase and scenario 4 °C increase and 20% precipitation reduction, the maximum and minimum annual runoff were increased by 81.9% and decreased by 70.9% compared with the baseline period, respectively. (4) Under the seven scenarios, the precipitation, temperature and runoff in the middle and late 21st century showed an increasing trend, and precipitation will be the main controlling factor affecting runoff. The annual runoff depth showed an increasing trend, and the change of runoff depth in the lower reaches of the basin will be the most obvious. [ABSTRACT FROM AUTHOR]

The establishment, development and abandonment and/or destruction of ancient civilizations were catalytically controlled by geomorphic features such as lakes and rivers and the climate. This paper examined the possible influence of tectonism and climate on six habitations of the ancient Vaigai River Basin civilization in South India, using multiple proxies such as grain size, geochronology and geochemistry of the sedimentary archives. The tectonic setting of the basin changed between the active margin and passive margin; the discriminant diagrams suggested varying provenance and changing climatic conditions over the mid‐ and‐late Holocene. Tectonic activism and quiescence, base‐level change in the channel morphology led to the burial/marooning of the first habitation surface. Overall, arid conditions were punctuated with catastrophic flooding and peak discharge (flood) destroyed the second, third and fourth habitation sites. These flooding events were characterized by moderate weathering (CIA) and high values of Al, Fe and Rb/Sr and low Ca/Mg in the sediment records. The abandonment/destruction of the fifth habitation also occurred during an arid interval (droughts), possibly caused by weak monsoon. Along with the interactions between tectono‐climatic and fluvial geomorphic factors, the new results provided avenues to (a) check and recognize the archives for 8.2 and 4.2 ka‐like events in this part of the world, and (b) the utility of integrated analyses to constrain on the civilizational histories of the mankind. [ABSTRACT FROM AUTHOR]

This research paper focuses on implementing two Nature-Based Solutions (NBS) in the Sarantapotamos river basin upstream of Magoula settlement, evaluating their effectiveness through flood hydrograph calculations before and after NBS, and under future climate scenarios, encompassing lower, mean, and upper conditions representing ± 95%. The study area covers an area of 226 km2 in Attica, Greece, susceptible to extreme flood events. The research contributes to NBS knowledge, emphasizing flood resilience and protecting settlements downstream. Land cover change and retention ponds, applied individually and combined, serve as NBS approaches. Flood hydrographs are calculated using the time–area (TA) diagram method in a geographic information system (GIS) with the Hydrological Engineering Center's Hydrological Modeling System (HEC-HMS). Results demonstrate NBS effectiveness in current climate conditions, reducing peak discharge by 9.3% and 28% for land cover change and retention ponds, respectively. The combined NBS achieves a 40.5% peak discharge reduction and a significant 15.7% total flood volume decrease. Under climate change scenarios, impacts on design precipitation and flood hydrographs vary. The upper climate change scenario exhibits a 3348% increase in peak discharge and a 600% rise in total flood volume, while the lower scenario sees a 44.6% reduction in total flood volume. In the mean climate change scenario, land cover change and retention ponds reduce peak discharge by 9.73% and 23.11% and total flood volume by 9.25% and 2.17%, respectively. In conclusion, retention ponds show substantial peak discharge reduction, while land cover changes extend the time to peak, emphasizing their potential in flood risk management. [ABSTRACT FROM AUTHOR]

This paper presents a validation of outputs from some GCMs of the CMIP6 project when used to assess climate projection and hydrological flows at a catchment scale for the case study area of the Lombardy region (Northern Italy). The modeling chain consists of (i) a choice of climatic scenarios from 10 GCMs of the CMIP6, (ii) the application of a stochastic downscaling procedure to make projections usable at the local scale, and (iii) the use of a semi-distributed physically based hydrological model Poli-Hydro for the generation of hydrological scenarios. Data on observed precipitation and temperature were collected from automatic weather stations, and the hydrological budget of four target catchments within the study area was assessed using Poli-Hydro. An ex-post (back-casting) analysis was performed upon the control data series from the GCMs by comparing statistics of relevant climate variables and model-simulated discharges against observed counterparts during the historical period 2002–2014. Then, during 2015–2021, the goodness of projections was assessed using confidence intervals. Our results show that the accuracy of GCMs in representing regional climate is not always reflected in a credible evaluation of local hydrology. The validation of climate patterns provides somewhat poor results; thus, the interaction among climate and hydrology needs to be explored carefully to warrant the credibility of hydrological scenarios. Overall, the spatial and temporal consistency of GCM projections, as explored here climatically and hydrologically, provides a clue about their dependability for basin scale management. [ABSTRACT FROM AUTHOR]

The Iberian Peninsula is a climate change hotspot, where the temperature is increasing faster than the global annual mean surface temperature, with the largest reduction of precipitation. Consequently, freshwater availability is expected to decrease substantially. In this context, freshwater systems are especially vulnerable in terms of meeting the water demands and ecosystem requirements we know today. In this paper, we present an extension of the eco-engineering decision scaling (EEDS) method to explore trade-offs in agricultural and ecologic metrics at the catchment scale across a range of unknown future hydrological and climate states. The extended EEDS method evaluates current water resource management rules focusing on agricultural and ecologic objectives, identifies climate hazards that make the system fail and assesses climate risk in three time horizons for the design of adaptation measures. The case study is the Serpis River basin, Spain, where 72% of available water is used for agricultural purposes. [ABSTRACT FROM AUTHOR]

Concurrent compound dry and hot events (CDHEs) amplified more damange on the ecosystems and human society than individual extremes. Under climate change, compound dry and hot events become more frequent on a global scale. This paper proposes a mathematical method to quantitatively attribute changes of CDHEs to changes of precipitation, change in temperature and change in the dependence between precipitation and temperature. The attribution is achieved by formulating the total differential equation of the return period of CDHEs among Meta-gaussian model. A case study of China is devised based on monthly precipitation and temperature data during the period from 1921 to 2020 for 80 major river basins. It is found that temperature is the main driving factor of increases in CDHEs for 49 major river basins in China, except for the upper and middle reaches of the Yangtze River. In West China, precipitation changes drove the increase in CDHEs in 18 river basins (23%), particularly in parts of North Xinjiang, Qinghai and Gansu. On the other hand, dependence between precipitation and temperature dominated changes of CDHEs in 13 river basins (16%) of China with other factors, including parts of South China, East China and Northwestern China. Furthermore, changes in both the mean and spread of precipitation and temperature can also contribute to changes in CDHEs. [ABSTRACT FROM AUTHOR]

Future water availability is threatened by changes in both climate and water demand. Water rights with differing priorities are an important foundation of demand‐side tools (e.g., buyback, water pricing, and water market) to improve water use efficiency and reduce water scarcity, especially in highly regulated river systems. This paper assesses the impact of climate change on water yields from carryover storage with dual‐priority (high/low) water rights allocation systems using a simple and rapid analytical method. The method characterizes reservoir inflows using readily available flow characteristics (annual mean and Cv). We evaluate this method against a water resource simulation model in the Goulburn River basin, Australia. In general, our analytical "dual‐priority" Gould‐Dincer model reproduces water allocation estimates from the simulation model. We further demonstrate this method across 12 Australian catchments to investigate the climate change impact on "dual‐priority" water rights yield at the catchment scale. The hydrological projections show decreasing mean annual runoff and increasing annual runoff variability, except for some catchments in northern Australia. Water yield for high‐priority water rights (HPWRs) and low‐priority water rights (LPWRs) decreases for most catchments except for some catchments in northern Australia. South Dandalup in the 2070s (RCP8.5) shows the largest percentage decrease in HPWR and LPWR yield (about −53.53% and −56.81%, respectively). Our results show that changes in mean annual inflow have a more significant influence on water yield of HPWR and LPWR than Cv. Overall, the simple method provides a rapid assessment of water yields with "dual‐priority" water rights which is applicable across multiple sites at regional or even global scale. Key Points: A simple analytical method is used to evaluate the impact of climate change on the yield of "dual‐priority" water rightsWater yield for both high‐ and low‐priority water rights generally decreases under future climate in AustraliaFuture change in mean annual inflow has a more significant influence on water yield than change in annual flow variability [ABSTRACT FROM AUTHOR]

Big-data mining approaches based on Artificial Intelligence models can help forecast biodiversity changes before they happen. These approaches can predict macroscopic species distribution patterns and trends that can inform preventive measures to avoid the loss of ecosystem functions and services. They can, therefore, help study and mitigate climate change implications on biodiversity conservation in fragile ecosystems. Wetlands are particularly fragile ecosystems where climate change poses severe risks and has dramatically reduced their size over the past century, with profound consequences on biodiversity and ecosystem services. Through big-data mining approaches, we can predict future wetland biodiversity trends in the context of climate change. This paper proposes such predictive analysis for a specific wetland: The Massaciuccoli Lake basin in Tuscany, Italy. This basin is a critical tourist attraction due to its rich biodiversity, making it an area of interest for citizens, tourists, and scientists. However, the region's suitability for native and non-native species is at risk due to climate and land-use change. Using machine-learning models, we predict the potential effects of climate change on animal spatial distribution in the basin under different greenhouse gas emission scenarios. The results suggest that habitat suitability has generally improved from 1950 to today, presumably owing to the targeted conservation strategies adopted in the area, but climate change will severely reduce bird biodiversity by 2050 while favouring several insect species' proliferation and other species' habitat change, even under a medium-emission scenario. This will lead to significant changes in the basin's biodiversity. Our methodology is adaptable to other wetland basins, being fully based on open data and models. The spatially explicit modelling used in this research provides valuable information for policymakers and spatial planners, complementing traditional biodiversity trend analyses. [Display omitted] • Bayesian Open Science ecological niche models for 180 species in an Italian wetland • Environmental change in the last 70 years has benefited animal biodiversity • Climate change will disadvantage birds even under medium greenhouse gas emission • Climate change will alter other species' richness and habitat distribution [ABSTRACT FROM AUTHOR]

The complex meso- and microclimatic heterogeneity inherent to mountainous regions, driven by both topographic and biotic factors, and the lack of observations, poses significant challenges to using climate models to predict and understand impacts at various scales. We present here a six-year dataset (2017–2022) of continuous climatic measurements collected at five elevations from 983 m to 2705 m above sea level in the Val Mazia - Matschertal valley in the Italian Alps. The measurements include the air temperature, relative humidity, wind speed and direction, solar radiation, soil properties, precipitation, and snow height. Collected within the European Long-Term Ecological Research program (LTER), this dataset is freely available in an open access repository. The time series may be valuable for the validation of regional climate models, atmospheric exchange modelling, and providing support for hydrological models and remote sensing products in mountain environments. Additionally, our data may be useful for research on the influence of elevation on ecological processes such as vegetation growth, plant composition, and soil biology. Beyond its utility in advancing such fundamental research, meteorological monitoring data contribute to informed socio-political decisions on climate adaptation strategies, land management, and water resource planning, enhancing the safety and resilience of mountain communities and biodiversity. [ABSTRACT FROM AUTHOR]

Using Mahanadi basin as a case, the study demonstrates benefit-sharing can improve water allocation among riparian states experiencing water stress. The results show the basin having a yearly average water deficit of 5429 million cubic metres (MCM) under business-as-usual which increases to 6781 MCM under high economic growth for 2011–2050. Even after various water supply augmentation and demand management interventions and climate change-induced increased runoff, the upper riparian state continues to have a water deficit. This can be reduced if the lower riparian state allows the upper one to divert 1500 MCM of additional water annually which will require a strong governance mechanism in place. [ABSTRACT FROM AUTHOR]

Semiarid regions play a pivotal role in global ecosystem and environmental governance. Changing environment (climate and land use variation) has led to the disruption of hydrology in semi-arid regions and ecological degradation in some area. Understanding their hydrological response to changing environments is crucial for ecological rehabilitation and optimal water resource allocation. This research, conducted in a Chinese semiarid watershed, integrates multi-field models about hydrology, meteorology and geography to investigate hydrological processes in typical hydrological years. The results indicate that the climate in this region is drying, and the likelihood of extreme weather events is increasing with global warming. Projecting changes from 2010 to 2060, 9.21% of grassland converting to 5.63% of forest and 3.58% of gully built-up land. As a result, the flood peak increases by 22.99% in typical drought years, while it decreases by 36.77% in normal years. Based on our analysis of the rainfallrunoff process in typical drought and normal years, we identify two distinct effects: the "local rainfall-runoff effect" and the "global rainfall-runoff effect", respectively. However, in typical wet years, the streamflow state is primarily controlled by intense and concentrated precipitation. This research provides insights into the effect of ecological restoration and typical climate variations on hydrological cycle in semiarid regions, thus contributing to more informed decision-making in environmental management and water resource planning. [ABSTRACT FROM AUTHOR]

Extreme heatwaves pose a significant threat to a wide range of environmental, ecological, and social systems. The rapid warming of the Arctic and the Tibetan Plateau (TP), which are the most prominent features in the Northern Hemisphere in the context of climate change, has significantly influenced mid-latitude extreme events in recent decades. This study utilizes observational data and numerical simulations to demonstrate that the variations in Arctic amplification (AA) and TP amplification (TA) play a crucial role in the interannual variability of summer heatwaves (HWs) in the Yangtze River Basin (YRB) (HWs_YRB) region. The HWs_YRB is associated with a zonally oriented barotropic high-pressure system anchored over the YRB region. The spatial distribution and intensity of the HWs_YRB are impacted by the synergistic effects of AA and TA, via a meridional atmospheric tripole pattern and double jets over East Asia. Furthermore, AA primarily impacts the geographical extent of the HWs_YRB, while TA plays a critical role in determining the intensity of the HWs_YRB. Our findings provide an innovative perspective on the linkage between the pronounced warming observed in the Arctic and TP and the occurrence of summer HWs_YRB, enhancing our comprehension of the climatic consequences of the rapid changes in these two geographical regions. [ABSTRACT FROM AUTHOR]

In the context of global climate change and ecological restoration projects, significant changes have been observed in the fractional vegetation cover (FVC) in the Yellow River basin. The increased vegetation growth accelerates water consumption, exacerbating drought and water scarcity issues, thereby heightening regional water resource shortage risks. This study targets the Yellow River basin in China, employing a pixel-based model to convert NDVI into FVC datasets. We establish a pixel-wise mathematical model for annual runoff and environmental factors based on residual analysis and methods like multiple linear regression. Using climate model data from CMIP6 as independent variables, in conjunction with the statistical model, we elucidate the spatiotemporal characteristics of annual runoff in the Yellow River basin under future climate scenarios. Our results indicate that, under four different climate scenarios, the average annual runoff in the Yellow River basin is projected to increase. The increases are quantified as 0.008 mm/a, 0.065 mm/a, 0.25 mm/a, and 0.24 mm/a for SSP126, SSP245, SSP370, and SSP585 scenarios, respectively. From 2022 to 2040, the spatial distribution of the runoff change rates under the SSP245 and SSP370 scenarios show an increasing trend in upstream areas such as the Qinhe and Longmen regions, with rates ranging from 6.00 to 8.61 mm/a. During the period from 2041 to 2060, all four climate scenarios indicate minimal changes in the runoff depth in the northern part of the Yellow River basin. From 2061 to 2080, under the SSP126 and SSP245 scenarios, the spatial distribution of the runoff shows significant increases in the river source area and a decreasing trend in the middle reaches, with rates ranging from 4.52 to 11.39 mm/a. For the period from 2081 to 2100, the runoff change rates vary significantly under the four climate scenarios. These findings provide a detailed understanding of how future climate scenarios could impact water resource distribution in the Yellow River basin, offering critical insights for regional water management and policy making to mitigate potential water scarcity challenges. [ABSTRACT FROM AUTHOR]

Civil infrastructure systems have traditionally been designed assuming stationarity in precipitation. However, climate change is making this assumption invalid, affecting both existing infrastructure designed assuming stationarity and the design of new infrastructure. Although many studies have analyzed potential increases in precipitation due to climate change, fewer have attempted to translate these changes into the impact of stream discharge in a way that could be incorporated into infrastructure design. Therefore, this study aimed to assess the potential impact of climate change on both rainfall and peak discharge to aid in bridge and road infrastructure design. Results showed that the median increase in model-derived rainfall intensity across the selected rainfall stations in Virginia was 10%–30% for the midcentury (centered on 2045) and 10%–40% for the end of the century (centered on 2085), with the higher increase for the Representative Concentration Pathway 8.5 (RCP8.5) scenario compared with the RCP4.5 scenario. A regression analysis was performed to relate peak discharge to watershed size for midcentury and end-of-century periods for the study area. In terms of peak discharge, smaller watersheds (<25 km2) had a percent increase for a given return period that was independent of the watershed size. Considering both RCP4.5 and RCP8.5 scenarios, for a 100-year return period, the increase was 39% and 49%, respectively, for the midcentury periods and 36% and 52%, respectively, for the end-of-century periods. For larger watersheds (>25 km2), the increase in peak discharge decreased as the watershed size increased, suggesting a dampening effect for larger watersheds in this coastal plain region of Virginia. For a watershed size of 1,700 km2 , the largest watershed included in the analysis, the percent increase in peak discharge for a 100-year return period was 14% and 39% during the midcentury, and 16% and 40% at the end of the century, for the two emission scenarios. These findings and the general methodology used in the study can aid transportation and water resources engineers in incorporating changing rainfall impacts into assessing current infrastructure and designing future infrastructure. They can also help to prioritize resources for more costly hydraulic analyses of potentially vulnerable infrastructure. The study aims to understand better how climate change will impact future precipitation and how this change in precipitation will impact peak discharge for watersheds of various sizes. Using Virginia as a study region, the median increase in precipitation intensity was found to be between 10% and 30% for the midcentury and 10%–40% for the end of the century across the state. Smaller watersheds (<25 km2) had an increase in peak discharge for a given return period that was independent of the watershed size. In comparison, larger watersheds (>25 km2) had an increase in peak discharge, but the percent increase in peak discharge decreased as the size of the watershed increased, especially for the RCP8.5 emission scenario. Regression equations were developed to provide a first approximation of peak discharge based on the watershed area, the emission scenario, and the return period to aid decision-makers in the region when including climate change impacts when assessing existing or designing new hydraulic structures. [ABSTRACT FROM AUTHOR]

Lakes are threatened by contemporary climate change and human activities. Paleohydrological records provide important evidence for developing scenarios for future changes in the availability of freshwater resources. This study presents a synthesis of a sedimentological, archeological, and chronological dataset collected from Lake Annecy (eastern France) to reconstruct a lake-level record documenting the whole Holocene. This dataset shows a pronounced minimum in the lake level during the Holocene thermal maximum (HTM) (ca. 9000–7000 cal BP), preceded by a general lowering trend (early Holocene), and followed by a general rising trend (Neoglacial). On both the millennial and centennial scales, the Lake Annecy record appears to match the regional pattern of Holocene lake-level fluctuations established for West-Central Europe. In agreement with other extra-regional paleoclimatic records, it shows the dominant influence of orbital forcing. The high magnitude of the lake-level lowering (more than 5 m) during the HTM, with a 2–2.5 °C difference between the HTM and the pre-industrial mean summer temperatures, suggests possible drastic lake-level lowering phases in the near future depending on the IPCC scenarios following climate change. This would mean dramatic impacts on human activities and the preservation of exceptional archeological remains in regional lake basins. [ABSTRACT FROM AUTHOR]

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

In recent decades, the depletion of surface water resources within the Lake Urmia Basin (LUB), Iran, has emerged as a significant environmental concern. Both anthropogenic activities and climate change have influenced the availability and distribution of surface water resources in this area. This research endeavors to provide a comprehensive evaluation of the impacts of climate change and anthropogenic activities on surface water resources across the LUB. Various critical climatic and anthropogenic factors affecting surface water bodies, such as air temperature (AT), cropland (CL), potential evapotranspiration (PET), snow cover, precipitation, built-up areas, and groundwater salinity, were analyzed from 2000 to 2021 using the Google Earth Engine (GEE) cloud platform. The JRC-Global surface water mapping layers V1.4, with a spatial resolution of 30 m, were employed to monitor surface water patterns. Additionally, the Mann–Kendall (MK) non-parametric trend test was utilized to identify statistically significant trends in the time series data. The results reveal negative correlations of −0.56, −0.89, −0.09, −0.99, and −0.79 between AT, CL, snow cover, built-up areas, and groundwater salinity with surface water resources, respectively. Conversely, positive correlations of 0.07 and 0.12 were observed between precipitation and PET and surface water resources, respectively. Notably, the findings indicate that approximately 40% of the surface water bodies in the LUB have remained permanent over the past four decades. However, there has been a loss of around 30% of permanent water resources, transitioning into seasonal water bodies, which now account for nearly 13% of the total. The results of our research also indicate that December and January are the months with the most water presence over the LUB from 1984 to 2021. This is because these months align with winter in the LUB, during which there is no water consumption for the agriculture sector. The driest months in the study area are August, September, and October, with the presence of water almost at zero percent. These months coincide with the summer and autumn seasons in the study area. In summary, the results underscore the significant impact of human activities on surface water resources compared to climatic variables. [ABSTRACT FROM AUTHOR]

The variations in snow cover on the Tibetan Plateau play a pivotal role in comprehending climate change patterns and governing hydrological processes within the region. This study leverages daily snow cover data and the NASA Digital Elevation Model (DEM) from 2003 to 2020 to analyze spatiotemporal snow cover days and assess their responsiveness to climatic shifts by integrating meteorological data. The results reveal significant spatial heterogeneity in snow cover across the Plateau, with a slight decreasing trend in annual average snow cover duration. Snow cover is predominantly observed during the spring and winter seasons, constituting approximately 32% of the total snow cover days annually. The onset and cessation of snow cover occur within a range of 120–220 days. Additionally, an increasing trend in snow cover duration below 5000 m altitude was observed, in addition to a decreasing trend above 5000 m altitude. Sub-basin analysis delineates the Tarim River Basin as exhibiting the lengthiest average annual snow cover duration of 83 days, while the Yellow River Basin records the shortest duration of 31 days. The decreasing trend in snow cover duration closely aligns with climate warming trends, characterized by a warming rate of 0.17 ± 0.54 °C per decade, coupled with a concurrent increase in precipitation at a rate of 3.09 ± 3.81 mm per year. Temperature exerts a more pronounced influence on annual snow cover duration variation compared to precipitation, as evidenced by a strong negative correlation (CC = −0.67). This study significantly augments the comprehension of hydrological cycle dynamics on the Tibetan Plateau, furnishing essential insights for informed decision-making in water resource management and ecological conservation efforts. [ABSTRACT FROM AUTHOR]

Mountain glaciers are considered natural indicators of warming and a device for climatic change. In addition, it is also a solid reservoir of freshwater resources. Along with climate change, clarifying the dynamic changes of glacier in the Aksu River Basin (ARB) are important for hydrological processes. The study examined the variations in glacier area, elevation, and their reaction to climate change in the ARB between 1990 and 2022. The glacier melt on the runoff is explored from 2003 to 2020. This investigation utilized Landsat and Sentinal-2 images, ICESat, CryoSat, meteorological and hydrological data. The findings suggest that: (1) The glacier area in the ARB retreated by 309.40 km2 (9.37%, 0.29%·a−1) from 1990 to 2022. From 2003 to 2021, the ARB glacier surface elevation retreat rate of 0.38 ± 0.12 m·a−1 (0.32 ± 0.10 m w.e.a−1). Comparison with 2003–2009, the retreat rate is faster from 2010 to 2021. (2) From 1990 to 2022, the Toxkan and the Kumalak River Basin's glacier area decreases between 61.28 km2 (0.28%·a−1) and 248.13 km2 (0.30%·a−1). Additionally, the rate of glacier surface elevation declined by −0.34 ± 0.11 m·a−1, −0.42 ± 0.14 m·a−1 from 2003 to 2021. (3) The mass balance sensitivities to cold season precipitation and ablation-phase accumulated temperatures are +0.27 ± 0.08 m w.e.a−1(10%)−1 and −0.33 ± 0.10 m w.e.a−1 °C−1, respectively. The mass loss is (962.55 ± 0.57) × 106 m3 w.e.a−1, (1087.50 ± 0.68) × 106 m3 w.e.a−1 during 2003–2009, 2010–2021 respectively. Warmer ablation-phase accumulated temperatures dominate glacier retreat in the ARB. (4) Glacier meltwater accounted for 34.57% and 41.56% of the Aksu River's runoff during the ablation-phase of 2003–2009 and 2010–2020, respectively. The research has important implications for maintaining the stability of water resource systems based on glacier meltwater. [ABSTRACT FROM AUTHOR]

The Vanj River Basin contains a dynamic glacier, the Medvezhiy glacier, which occasionally poses a danger to local residents due to its surging, flooding, and frequent blockages of the Abdukahor River, leading to intense glacial lake outburst floods (GLOF). This study offers a new perspective on the quantitative assessment of glacier surface velocities and associated lake changes during six surges from 1968 to 2023 by using time-series imagery (Corona, Hexagon, Landsat), SRTM elevation maps, ITS_LIVE, unmanned aerial vehicles, local climate, and glacier surface elevation changes. Six turbulent periods (1968, 1973, 1977, 1989–1990, 2001, and 2011) were investigated, each lasting three years within a 10–11-year cycle. During inactive phases, a reduction in the thickness of the glacier tongue in the ablation zone occurred. During a surge in 2011, the flow accelerated, creating an ice dam and conditions for GLOF. Using these datasets, we reconstructed the process of the Medvezhiy glacier surge with high detail and identified a clear signal of uplift in the surface above the lower glacier tongue as well as a uniform increase in velocities associated with the onset of the surge. The increased activity of the Medvezhiy glacier and seasonal fluctuations in surface runoff are closely linked to climatic factors throughout the surge phase, and recent UAV observations indicate the absence of GLOFs in the glacier's channel. Comprehending the processes of glacier movements and related changes at a regional level is crucial for implementing more proactive measures and identifying appropriate strategies for mitigation. [ABSTRACT FROM AUTHOR]

Located in the central part of the arid regions of Northwest China, the Heihe River Basin (HRB) plays an important role in wind prevention, sand fixation, and soil and water conservation as the second largest inland river basin. In the context of the warming and wetting climate observed in Northwest China, the situation of the ecological environment in the HRB is of significant concern. Using the data from meteorological observation stations, grid fusion and hydrological monitoring, this study analyzes the multi-scale climate changes in the HRB and their impacts on runoff. In addition, predictive models for runoff in the upper and middle reaches were developed using machine learning methods. The results indicate that the climate in the HRB has experienced an overall warming and wetting trend over the past 60 years. At the same time, there are clear regional variabilities in the climate changes. Precipitation shows decreasing trends in the northwestern part of the HRB, while it shows increases at rates higher than the regional average in the southeastern part. Moreover, the temperature increases are generally smaller in the upper reaches than those in the middle and lower reaches. Over the past 60 years, there has been a remarkable increase in runoff at the Yingluo Gorge (YL) hydrological station, which exhibits a distinct "single-peak" pattern in the variation of monthly runoff. The annual runoff volume at the YL (ZY) hydrological station is significantly correlated with the precipitation in the upper (middle) reaches, indicating the precipitation is the primary influencing factor determining the annual runoff. Temperature has a significant impact only on the runoff in the upper reaches, while its impact is not significant in the middle reaches. The models trained by the support vector machines and random forest models perform best in predicting the annual runoff and monthly runoff, respectively. This study can provide a scientific basis for environmental protection and sustainable development in the HRB. [ABSTRACT FROM AUTHOR]

The long-term record of ecological, limnological and climatological parameters that were documented in the Kinneret drainage basin was statistically evaluated. The dependent relations between environmental parameters and a change in climate conditions open a consequence dispute between three optional definitions: long-term instability, climate change impact and ecosystem resiliency. The Kinneret drainage basin during the Anthropocene era is marked by intensive anthropogenic involvement: Increase in population size, drainage of the wetlands and old lake Hula, agricultural development, enhancement of lake Kinneret utilization for water supply, hydrological management, fishery and recreation. Therefore, the impact of a combination of natural and anthropogenic environmental factors confounded each other, and the uniqueness of climate change is unclear. [ABSTRACT FROM AUTHOR]

Continued urban expansion (UE) has long been regarded as a huge challenge for climate change mitigation. However, much less is known about how UE affects carbon emissions (CEs), especially in the urban agglomerations of the Yellow River Basin (UAYRB), China. In this regard, this study introduced kernel density analysis, the Gini coefficient, and Markov chains to reveal the UE patterns and carbon emissions intensity (CEI) in the UAYRB at the county level, and explored the spatial heterogeneity of the impact of UE on CEI with the geographically and temporally weighted regression model. The results show that both CEI and UE in the UAYRB showed a steady growing trend during the study period. The kernel density of CEI and UE revealed that CEI in the UAYRB was weakening, while the UE rate continuously slowed down. The Gini coefficients of both CEI and UE in the UAYRB region were at high levels, indicating obvious spatial imbalance. The Markov transfer probability matrix for CEI with a time span of five years showed that CEI growth will still occur over the next five years, while that of UE was more obvious. Meanwhile, counties with a regression coefficient of UE on CEI higher than 0 covered the majority, and the distribution pattern remained quite stable. The regression coefficients of different urban landscape metrics on CEI in the UAYRB varied greatly; except for the landscape shape index, the regression coefficients of the aggregation index, interspersion and juxtaposition index, and patch density overall remained positive. These findings can advance the policy enlightenment of the high-quality development of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

This article provides high-resolution information on the projected changes in annual extreme rainfall and high- and low-streamflow events over Southeast Asia under extreme climate change. The analysis was performed using the bias-corrected result of the High-Resolution Model Intercomparison Project (HighResMIP) multi-model experiment for the period 1971–2050. Eleven rainfall indices were calculated, along with streamflow simulation using the PCR-GLOBWB hydrological model. The historical period 1981–2010 and the near-future period 2021–2050 were considered for this analysis. Results indicate that, over former mainland Southeast Asia, Myanmar will face more challenges in the near future. The east coast of Myanmar will experience more extreme high-rainfall conditions, while northern Myanmar will have longer dry spells. Over the Indonesian maritime continent, Sumatra and Java will suffer from an increase in dry-spell length of up to 40 %, while the increase in extreme high rainfall will occur over Borneo and mountainous areas in Papua. Based on the streamflow analysis, the impact of climate change is more prominent in a low-flow event than in a high-flow event. The majority of rivers in the central Mekong catchment, Sumatra, Peninsular Malaysia, Borneo, and Java will experience more extreme low-flow events. More extreme dry conditions in the near future are also seen from the increasing probability of future low-flow occurrences, which reaches 101 % and 90 %, on average, over Sumatra and Java, respectively. In addition, based on our results over Java and Sumatra, we found that the changes in extreme high- and low-streamflow events are more pronounced in rivers with steep hydrographs (rivers where flash floods are easily triggered), while rivers with flat hydrographs have a higher risk in terms of the probability of low-flow change. [ABSTRACT FROM AUTHOR]

Frequent drought disasters have significant impacts on socio-economic and ecosystems, and it is crucial to explore the propagation characteristics of drought for disaster prevention and mitigation. In this paper, based on 0.25° × 0.25° grid-point Meteorological hydrological and large-scale climate factor data, the start-to-start, peak-to-peak, and end-to-end drought propagation times, and the periods and rates of drought development and recovery were estimated for 11 regions in the Luanhe River Basin under stationary and non-stationary conditions. The Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework was used to construct stationary and non-stationary models to capture the stationary and non-stationary drought characteristics respectively, and then the drought development and recovery patterns, and drought propagation times were assessed. The results showed that under the influence of climate factors, severe drought events occurred in most study areas, the duration of meteorological drought was prolonged by 0.1–0.6 months, and the peak intensity was increased by about 0.05. The severity of hydrological drought increased by 0.2–0.8, and the peak intensity decreased by 0.1–0.2. The rate of development and recovery of hydrological drought was accelerated by 0.1–0.2 per month. The propagation time of start-to-start was shortened by 0.2 months, and the propagation time of end-to-end was extended by 1–2 months. These mean that water resource control authorities need to propose responses to droughts more quickly. • The non-stationary drought indices considering climatic factors were constructed. • The drought propagation time was calculated from start to start, peak to peak, and end to end. • Quantification of the effects of climate change on drought propagation [ABSTRACT FROM AUTHOR]

Climate change led an increase in the frequency of severe droughts, the effects of which are exacerbated by a lack of water storage. Despite increasing research on global-scale total water storage (TWS) change and drought prediction, basin-scale long-term hydrological drought, TWS change, and El Nino–Southern Oscillation (ENSO) influence in East Africa (EA) remain unexplored. In this paper, we used multiple approaches, of ensemble machine learning (ML) and weighted averaging, to conduct a basin-scale exploratory analysis of future hydrological drought and TWS change for the period 2025–2099. Climate change will affect future hydrological conditions in the basins, with maximum severity values of −90.3, −726.6, and −2567.7 Gt in the Tana, Turkana, and Victoria basins, respectively, under RCP6.0. Similarly, we found maximum severities of −187.5 and −277.7 Gt in the Abaya-Chamo and Tanganyika basins, respectively, under RCP 2.6. The most severe El Nino drought and exceptional La Nina conditions in the basins were found under both RCP scenarios. To ensure future water security in EA, sustainable water resource management strategies that can mitigate the impacts of extreme climate events in the future are urgently needed. [ABSTRACT FROM AUTHOR]

Water erosion, a notorious major threat to food security and ecosystem sustainability, is strongly conditioned by spatial and temporal scale effects. This paper systematically reviews the scale issues in runoff and sediment delivery (SIRSD) as a research field by integrating the traditional review approach and bibliometric analysis. This review summarises SIRSD's roots and the scale effect on runoff and sediment delivery. Then, we provide quantitative insights into the SIRSD domain's development history, thematic structure, geographic distribution, international cooperation, and methodologies. Findings show that: i) SIRSD arises from the gap between the non-linearity of runoff and sediment delivery across scales and our ability to measure it. Point-based and short-term measurements cannot capture the non-linearities from the spatio-temporal heterogeneities and cross-scale interactions of factors or processes. ii) Previous literature provides evidence that the spatial scaling of specific runoff (r), soil erosion (SE), sediment yield (SSY), or sediment delivery ratio (SDR) with drainage area (A) or slope length (L) exhibits contrasting patterns due to distinct mechanisms. Infiltration-excess and saturation-excess processes account for inverse and positive r - A relations, respectively. Interrill-erosion and rill-erosion cause inverse and positive SE-L relations. Hillslope-erosion and channel/bank-erosion explain inverse and positive SSY-A relations. Downstream increasing deposition and additional sediment inputs drive inverse and positive SDR-A relations. These scaling relationships can be nonlinear or complex due to spatial heterogeneities in land use, vegetation, topography, climate, lithology, and soil characteristics. Hence, applying an empirical scaling equation developed from the region with distinct environmental contexts is not recommended. Furthermore, the existing scaling patterns or equations may require updating given global climate and land use change. iii) SIRSD is a complex and multidisciplinary issue investigated by scientists from 93 countries since 1928. International research has substantially facilitated the understanding of SIRSD; still, more collaboration should focus on less-developed countries with high soil and water loss risks and urgent conservation needs, such as those in Africa and South America under cropland expansion. iv) Scale mismatch and scale break have discredited large-scale erosion and sediment assessments. Incorporating gully and bank erosion into modelling, extending the scale range of the L factor, and expanding the sediment scaling scope from watershed to slope may make a difference. Therefore, more research with nested design incorporating multiple scales is necessary for cross-scale analysis and scalable modelling. Addressing global climate change requires improving real-time urban flood forecasting and integrating downscaled climate models with hydrology, erosion, and sediment transport models. • A bibliometric review of the global SIRSD research for the first time. • SIRSD is rooted in the gap between natural nonlinearity and our measuring ability. • Scaling of specific runoff, erosion, sediment yield, and SDR has diverse patterns. • Scale mismatch and scale break discredit large-scale modelling and assessments. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ten multi-model combination methods (MMCMs) are created from 29 models in 50 basins. • MMCMs improve some performance indicators, especially the Granger-Ramanathan method. • MMCMs do not improve performance in reproducing distributions of hydrological signatures. • Application with series of targeted signatures does not improve MMCM performance. • MMCM performance is improved by selecting more robust candidate models for ensembles. Multi-model combination (averaging) methods (MMCMs) are used to improve the accuracy of hydrological (precipitation-runoff) outputs in simulation or forecasting/prediction modes. In this paper, we examined if the application of MMCMs can improve model performance in reproducing distributions of hydrological signatures, such as annual maxima or minima of varying durations. To this end, ten MMCMs were applied to 29 bucket-type models to simulate runoff in 50 high-latitude catchments. The MMCMs were evaluated by comparing the resulting simulated flows to the reference (i.e., best-performing) individual model, considering various commonly used performance indicators, as well as model performance in reproducing the distributions of signatures. Additionally, we analysed whether (1) the selection of the candidate models, or (2) targeting specific signatures, such as annual maxima or minima, can improve performance of the model combinations. The results suggest that the application of MMCMs can improve accuracy of runoff simulations in terms of traditional performance indicators, but fails to improve performance in reproducing the distributions of signatures. Neither excluding poor-performing models nor applying the MMCMs with the targeted signatures, improves this aspect of model performance. These findings clearly reveal the need for further research aiming at enhancing model performance in reproducing the distributions of hydrological signatures, which is essential for climate-change impact studies. [ABSTRACT FROM AUTHOR]

Climate change has intensified the effects of habitat fragmentation in many ecosystems, particularly exacerbated in riparian habitats. Therefore, there is an urgent need to identify keystone connectivity spots to ensure long-term conservation and sustainable management of riparian systems as they play a crucial role for landscape connectivity. This paper aims to identify critical areas for connectivity under two contrasting climate change scenarios (RCP 4.5 and RCP 8.5 models) for the years 2030, 2050 and 2100 and to group these critical areas by similar connectivity in keystone spots for sustainable management. A set of analyses comprising climate analysis, drainage network analysis, configuration of potential riparian habitats, riparian habitat connectivity, data clustering, and statistical analysis within a Spanish river basin (NW Spain) were applied. The node and link connectivity would be reduced under the two climate change scenarios (≈2.5 % and 4.4 % reduction, respectively), intensifying riparian habitat fragmentation. Furthermore, 51 different clusters (critical areas) were obtained and classified in five classes (keystone spots) with similar connectivity across the different scenarios of climate change. Each keystone spot obtained by hierarchical classification was associated with one or more climate scenarios. One of these keystone spots was especially susceptible to the worst climate change scenario. Key riparian connectivity spots will be crucial for the management and restoration of highly threatened riparian systems and to ensure long-term biodiversity conservation. • Connectivity importance was reduced under different climate change scenarios. • Critical area detection for connectivity conservation is threatened by climate change. • Critical areas were classified with similar connectivity keystone spots against climate change. • Keystone spots with high PC index will be priority for conservation management. [ABSTRACT FROM AUTHOR]

Global warming is caused by rising carbon dioxide concentrations, while ecological and environmental issues are becoming increasingly evident. Many governments' main objective in addressing climate challenges is to achieve carbon balance. Exploring the distribution and changing trends of carbon balance can contribute to carbon balance strategies. This study takes the Yangtze River Economic Belt (YREB) as the study area, analyzing the spatial and temporal dynamic changes in carbon emissions and carbon sequestration in the YREB from 2000 to 2017. The county-level supply–demand ratios and accessibility are calculated based on the enhanced two-step floating catchment method according to the dynamic flow radius. According to our experimental results, carbon emissions can achieve different degrees of carbon balance according to the flow radius. After carbon emissions flow between counties within the province, some provinces can realize the transition from carbon surplus to carbon balance. With the expansion of the flow radius and the increase in internal mobility, more counties can participate in carbon sequestration, and some provinces can achieve carbon neutrality after carbon emissions transfer across provinces. Hubei, Chongqing, Zhejiang, Hunan and other provinces with special carbon sequestration capacity are very sensitive to changes in the radius of carbon emission flow. In 2017, when the carbon emission flow radius is 50 km, the net carbon emission of the flow can be reduced by 3%. If the radius is increased to 200 km, the YREB can achieve carbon balance. This study can provide decision-making information for carbon emission ecosystem management in the YREB. [ABSTRACT FROM AUTHOR]

This study examined the impacts of climate change and human activities on runoff within the Feiling Hydrological Station watershed in the Qinhe River basin, utilizing the SWAT (Soil and Water Assessment Tool) model. Several climate change and extreme land-use scenarios were evaluated for their effects on runoff. Results demonstrated the SWAT model's suitability for runoff simulation in the watershed, revealing a negative correlation between runoff and temperature changes, and a positive correlation with precipitation changes. Significantly, runoff responses to precipitation variations of ±10% and ±20% were more marked than those to temperature changes of ±1 °C and ±2 °C. In scenarios of extreme woodland and fallow land, runoff decreased, whereas in scenarios of extreme cropland and grassland, it increased, particularly in the extreme farmland scenario. The study's findings are important for the sensible management of soil and water resources and the enhancement of the natural environment in the studied area. [ABSTRACT FROM AUTHOR]

We analyzed hydrological responses to changing climate and land use/land cover (LULC) for the past (1985–2020) and future (2021–2080) in the Chemoga watershed of the Upper Blue Nile Basin. The watershed comprises four agroecological environments: Moist Kolla, Moist Weyna Dega, Moist Dega, and Wet Wurch. Past and projected LULC changes under business-as-usual (BAU) and land conservation (LC) scenarios were utilized. Climate projections from 2021 to 2080, under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5), were downscaled from Global Climate Models. Utilizing the Soil and Water Analysis Tool, we assessed impacts on mean annual surface runoff (SR) and evapotranspiration (ET). Maximum and minimum temperatures increased significantly in the past and future climate scenarios, with a significant rainfall increase observed under SSP5-8.5. Historical trends revealed a 16.6% increase in SR and 7% in ET from 1983–2002 to 2003–2020. Under BAU LULC with the SSP2-4.5 (SSP5-8.5) climate scenario, SR increased by 24% (26.1%) and ET by 3.1% (4.4%) from 2003–2020 to 2021–2050, followed by a subsequent SR rise of 13.7% (14.0%) and ET increase of 6.0% (5.7%) from 2021–2050 to 2051–2080. Conversely, the LC LULC with SSP2-4.5 (SSP5-8.5) resulted in a 5.3% (4.2%) SR decrease and ET increase of 9.7% (11.3%) from 2003–2020 to 2021–2050 and a further SR decrease of 1% (0.7%) and 6.1% (6.9%) ET increase from 2021–2050 to 2051–2080. The Moist Kolla agroecology experienced the highest SR increase due to vegetation clearances for commercial farming. Meanwhile, the LC scenario indicated substantial decreases in SR and marginal increases in ET in the Moist Weyna Dega agroecology due to forest restoration on steep slopes. Overall, SR showed greater sensitivity to LULC changes, while ET was more responsive to climate changes. The results emphasize considering diverse agroecological contexts for effective water resource management under changing climate and LULC scenarios. [ABSTRACT FROM AUTHOR]

This study evaluated the impacts of climate change on hydro-meteorological droughts in the Chao Phraya River Basin (CPRB), Thailand under two Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5). We used three Reginal Climate Models (RCMs) of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment—Southeast Asia (SEACLID/CORDEX-SEA), which are bias corrected. The Soil and Water Assessment Tool (SWAT) was used to simulate streamflow for future periods. The Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were estimated and used for drought characterization at three time scales (3, 6, and 12 months). The lag time between meteorological and hydrological droughts is approximately 1–3 months. The results suggest that the CPRB is likely to experience less frequent hydro-meteorological drought events in the future. The meteorological drought is projected to be longer, more severe, and intense. The severity of hydrological drought tends to decrease, but the intensity could increase. Climate change has been discovered to alter drought behaviors in the CPRB, posing a threat to drought monitoring and warning because droughts will be less predictable in future climate scenarios. The characterization of historical and future droughts over the CPRB is therefore valuable in developing an improved understanding of the risks of drought. [ABSTRACT FROM AUTHOR]