Hydrological Cycle Research Articles

Impact of Climate Change on the Environment: A Synthesis Study

Climate change has a significant impact on both physical and social components of the environment. Every component of the environment has been suffering the impacts of climate change. All components of the environment are interrelated through the exchanging of energy and matter; hence they actively interact. Major components of the environment like the biosphere, lithosphere, atmosphere, and hydrosphere are open systems to impact climate change. This paper describes the major impacts of climate change on major components of the environment. This study investigated the current state, wide-range global research trends, and different concerns on the impacts of climate change on the sustainable tourism. Global climate change represents a grand challenge for society, one that is increasingly influencing tourism sector investment, planning, operations, and demand. This study synthesized a total of 36 studies on climate change by sourcing published material from the review that was performed in indexed databases namely Dimensions, Web Science, Elsevier Scopus, and Google Scholar. Therefore, the study found that human beings are the major contributors to climate change through anthropogenic greenhouse gas emissions that worsened during the Green Revolution. Climate change outcomes through the loss of valuable ecosystem goods and services, degrading the most of keystone species sites. In other ways, loss of biodiversity, changes in atmospheric composition, changes in chemical reactions in soil, changes in water quality, availability, and hydrologic cycles, and frequent occurrence of extreme weather conditions. Of course! The effects of climate change are wide-ranging and diverse, impacting many areas and facets of daily life. Therefore, this study recommends implementing carbon pricing mechanisms to internalize the costs of greenhouse gas emissions and enforcing stringent environmental regulations and standards to limit emissions and pollution. Support global efforts and agreements to combat climate change, such as the Paris Agreement.

Flood Propagation Characteristics in a Plain Lake: The Role of Multiple River Interactions

Plain lakes play a crucial role in the hydrological cycle of a watershed, but their interactions with adjacent rivers and downstream water bodies can create complex river–lake relationships, often leading to frequent flooding disasters. Taking Poyang Lake as an example, this paper delves into its interaction with the Yangtze River, revealing the spatiotemporal patterns of flood propagation within the lake and its impact on surrounding flood control measures. The aim is to provide insights for flood management in similar environments worldwide. This study employs a comprehensive approach combining hydrological statistical analysis and two-dimensional hydrodynamic modeling, based on extensive hydrological, topographic, and socio-economic data. The results indicate that the annual maximum outflow from Poyang Lake is primarily controlled by floods within the watershed, while the highest annual lake water level is predominantly influenced by floods from the Yangtze River. The peak discharge typically reaches the lake outlet within 48 h, with the peak water level taking slightly longer at 54 h. However, water storage in the lake can shorten the time that it takes for the peak discharge to arrive. When converging with floods from the Yangtze River, the peak water level may be delayed by up to 10 days, due to the top-supporting interaction. Furthermore, floods from the “Five Rivers” propagate differently within the lake, affecting various lake regions to differing degrees. Notably, floods from the Fu River cause the most significant rise in the lake’s water level under the same flow rate. The top-supporting effect from the Yangtze River also significantly impacts the water surface slope of Poyang Lake. When the Yangtze River flood discharge significantly exceeds that of the “Five Rivers” (i.e., when the top-supporting intensity value, f, exceeds four), the lake surface becomes as flat as a reservoir. During major floods in the watershed, the water level difference in the lake can increase dramatically, potentially creating a “dynamic storage capacity” of up to 840 million cubic meters.

Feature Variable Selection Based on VIS-NIR Spectra and Soil Moisture Content Prediction Model Construction

The hydrological cycle, surface energy balance, and the management of water resources are all significantly impacted by soil moisture. Because it governs the physical processes of evapotranspiration and rainfall penetration, surface soil moisture is a significant climatic variable. In this work, visible-near infrared (VIS-NIR) bands were used to compare and analyze the spectra of loess samples with varying moisture concentrations. The investigation looked at how changes in the soil moisture content impacted the response of the soil spectra. The researchers used a genetic algorithm (GA), interval combination optimization (ICO), and competitive adaptive reweighted sampling (CARS) to filter feature variables from full-band spectral data. To forecast the moisture content of loess on the soil surface, models like partial least squares regression (PLSR), support vector machine (SVM), and random forest (RF) were created. The findings indicate that: (1) the most reliable spectrum preprocessing technique is the first derivative (FD), which can significantly enhance the model’s prediction power and spectral characteristic information. (2) The feature band selection method’s prediction effect of soil moisture content is typically superior to that of full-spectrum data. (3) The random forest (RF) prediction model for soil moisture content with the highest accuracy was built by combining the genetic algorithm (GA) with the FD preprocessed spectra. The results may provide a new understanding on how to use VIS-NIR to measure soil moisture content.

Verification of Long‐Term Ensemble Evapotranspiration Hindcast Using a Conditional Nonlinear Optimal Parameter Perturbation Ensemble Prediction Method on the Tibetan Plateau

AbstractIn this research, a conditional nonlinear optimal perturbation related to parameters (CNOP‐P) method is employed to propose an ensemble prediction method titled as the conditional nonlinear optimal perturbation related to parameters ensemble prediction (CNOP‐PEP) method. Within the CNOP‐PEP method, all ensemble members are generated by the CNOP‐P method. To explore the operability and validity of the CNOP‐PEP method, long‐term evapotranspiration (ET) hindcast skill is evaluated at 13 sites on the Tibetan Plateau (TP) during the period of 2001–2018 with a land surface model. Two traditional ensemble prediction methods (the stochastically perturbed parameters (SPP) method and the one‐at‐a‐time (OAT) method) are also applied to assess the ET hindcast skills. The numerical results indicate that the CNOP‐PEP method shows the best hindcast skill for estimated ET at 13 stations on the TP among the three methods (CNOP‐PEP, OAT, and SPP methods) during the period of 2001–2018. This suggests that the CNOP‐PEP method is helpful and effective for long‐term and interannual hydrological predictions, such as long‐term and interannual ET predictions. The numerical results also indicate that ensemble members with certain special properties of fast‐growing types should be selected to implement ensemble prediction compared to these ordinary and traditional samples. The CNOP‐PEP method could supply special samples to improve the ensemble prediction and hindcast skill of hydrological cycle.

Global total precipitable water variations and trends over the period 1958–2021

Abstract. Global responses of the hydrological cycle to climate change have been widely studied, but uncertainties still remain regarding water vapor responses to lower-tropospheric temperature. Here, we investigate the trends in global total precipitable water (TPW) and surface temperature from 1958 to 2021 using ERA5 and JRA-55 reanalysis datasets. We further validate these trends using radiosonde from 1979 to 2019 and Atmospheric Infrared Sounder (AIRS) and Special Sensor Microwave Imager/Sounder (SSMIS) observations from 2003 to 2021. Our results indicate a global increase in total precipitable water (TPW) of ∼ 2 % per decade from 1993–2021. These variations in TPW reflect the interactions of global warming feedback mechanisms across different spatial scales. Our results also revealed a significant near-surface temperature (T2 m) warming trend of ∼ 0.15 K decade−1 over the period 1958–2021. The consistent warming at a rate of ∼ 0.21 K decade−1 after 1993 corresponds to a strong water vapor response to temperature at a rate of 9.5 % K−1 globally, with land areas warming approximately twice as fast as the oceans. The relationship between TPW and T2 m showed a variation of around 6 % K−1–8 % K−1 in the 15–55° N latitude band, aligning with theoretical estimates from the Clausius–Clapeyron equation.

Contribution of fluorescent primary biological aerosol particles to low-level Arctic cloud residuals

Abstract. Mixed-phase clouds (MPCs) are key players in the Arctic climate system due to their role in modulating solar and terrestrial radiation. Such radiative interactions rely, among other factors, on the ice content of MPCs, which is regulated by the availability of ice-nucleating particles (INPs). While it appears that INPs are associated with the presence of primary biological aerosol particles (PBAPs) in the Arctic, the nuances of the processes and patterns of INPs and their association with clouds and moisture sources have not been resolved. Here, we investigated for a full year the abundance of and variability in fluorescent PBAPs (fPBAPs) within cloud residuals, directly sampled by a multiparameter bioaerosol spectrometer coupled to a ground-based counterflow virtual impactor inlet at the Zeppelin Observatory (475 m a.s.l.) in Ny-Ålesund, Svalbard. fPBAP concentrations (10−3–10−2 L−1) and contributions to coarse-mode cloud residuals (0.1 to 1 in every 103 particles) were found to be close to those expected for high-temperature INPs. Transmission electron microscopy confirmed the presence of PBAPs, most likely bacteria, within one cloud residual sample. Seasonally, our results reveal an elevated presence of fPBAPs within cloud residuals in summer. Parallel water vapor isotope measurements point towards a link between summer clouds and regionally sourced air masses. Low-level MPCs were predominantly observed at the beginning and end of summer, and one explanation for their presence is the existence of high-temperature INPs. In this study, we present direct observational evidence that fPBAPs may play an important role in determining the phase of low-level Arctic clouds. These findings have potential implications for the future description of sources of ice nuclei given ongoing changes in the hydrological and biogeochemical cycles that will influence the PBAP flux in and towards the Arctic.

Evapotranspiration in the Amazon Basin: Couplings, hydrological memory and water feedback

The hydrological cycle of the Amazon Basin is characterized by a multitude of interactions between the atmosphere and surface processes, involving several temporal and spatial scales. Evapotranspiration is a key variable in the water and energy balance, particularly in this watershed that is home to the world largest rainforest. This study analyzed evapotranspiration in the Amazon Basin using the concepts of Coupling (one way relationship between two variables), Memory (temporal permanence of a state or anomaly in the behavior of one variable) and Feedback (two way relationships between two variables), during a 62-year period (12/1959–11/2021). This study found that the seasonality of precipitation, mainly due to the South American Monsoon, determines when evapotranspiration is mainly driven by (or coupled with) net radiation at the surface or soil moisture. Moreover, in the regions where seasonality of precipitation is strong, the previous hydroclimatic conditions due to hydrological memory (reaching just over 90 days in shallow soils) influences the evapotranspiration during the relatively dry season. Regarding water feedback, this study found that the dependence of seasonal precipitation of the Amazon Basin from their hydrobiological processes (fraction of precipitation recycled by Amazonian evapotranspiration) increases with the distance from the Atlantic Ocean, mainly during the non-monsoonal circulation. This process is particularly remarkable in the Amazon-Andes transition zone. However, the spatial pattern and height of water recycled in this watershed is mainly determined by the dominant circulation pattern of atmospheric fluxes in each season.

Remote Sensing and Modeling of the Cryosphere in High Mountain Asia: A Multidisciplinary Review

Over the past decades, the cryosphere has changed significantly in High Mountain Asia (HMA), leading to multiple natural hazards such as rock–ice avalanches, glacier collapse, debris flows, landslides, and glacial lake outburst floods (GLOFs). Monitoring cryosphere change and evaluating its hydrological effects are essential for studying climate change, the hydrological cycle, water resource management, and natural disaster mitigation and prevention. However, knowledge gaps, data uncertainties, and other substantial challenges limit comprehensive research in climate–cryosphere–hydrology–hazard systems. To address this, we provide an up-to-date, comprehensive, multidisciplinary review of remote sensing techniques in cryosphere studies, demonstrating primary methodologies for delineating glaciers and measuring geodetic glacier mass balance change, glacier thickness, glacier motion or ice velocity, snow extent and water equivalent, frozen ground or frozen soil, lake ice, and glacier-related hazards. The principal results and data achievements are summarized, including URL links for available products and related data platforms. We then describe the main challenges for cryosphere monitoring using satellite-based datasets. Among these challenges, the most significant limitations in accurate data inversion from remotely sensed data are attributed to the high uncertainties and inconsistent estimations due to rough terrain, the various techniques employed, data variability across the same regions (e.g., glacier mass balance change, snow depth retrieval, and the active layer thickness of frozen ground), and poor-quality optical images due to cloudy weather. The paucity of ground observations and validations with few long-term, continuous datasets also limits the utilization of satellite-based cryosphere studies and large-scale hydrological models. Lastly, we address potential breakthroughs in future studies, i.e., (1) outlining debris-covered glacier margins explicitly involving glacier areas in rough mountain shadows, (2) developing highly accurate snow depth retrieval methods by establishing a microwave emission model of snowpack in mountainous regions, (3) advancing techniques for subsurface complex freeze–thaw process observations from space, (4) filling knowledge gaps on scattering mechanisms varying with surface features (e.g., lake ice thickness and varying snow features on lake ice), and (5) improving and cross-verifying the data retrieval accuracy by combining different remote sensing techniques and physical models using machine learning methods and assimilation of multiple high-temporal-resolution datasets from multiple platforms. This comprehensive, multidisciplinary review highlights cryospheric studies incorporating spaceborne observations and hydrological models from diversified techniques/methodologies (e.g., multi-spectral optical data with thermal bands, SAR, InSAR, passive microwave, and altimetry), providing a valuable reference for what scientists have achieved in cryosphere change research and its hydrological effects on the Third Pole.

Anthropogenic forcings reverse a simulated multi-century naturally-forced Northern Hemisphere Hadley cell intensification

The Hadley circulation plays a central role in determining the location and intensity of the hydrological cycle in tropical and subtropical latitudes. Thus, the human-induced historical and projected weakening of the Northern Hemisphere Hadley circulation has considerable societal impacts. Yet, it is currently unknown how unparalleled this weakening is relative to the response of the circulation to natural forcings in past centuries. Here, using state-of-the-art climate models, we show that in contrast to the recent and future human-induced Hadley circulation weakening, natural forcings acted to intensify the circulation by cooling the climate over the last millennium. The reversal of a naturally-forced multi-centennial trend by human emissions highlights their unprecedented impacts on the atmospheric circulation. Given the amplifying effect of natural forcings on the Hadley circulation, our analysis stresses the importance of adequately incorporating natural forcings in climate model projections to better constrain future tropical climate changes.

Spatiotemporal Variations in Snow Cover on the Tibetan Plateau from 2003 to 2020

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.

Magnesium Isotopes of Carbonate Reveal Seasonal Climate Variation in the Central East Asia During the Middle Eocene

AbstractIt is debated whether there was strong climate seasonality during the Eocene, which provides a close geological analogy for near‐future scenarios of greenhouse gas emissions. Lithological data suggest the existence of a broad arid zone centered around 30°N paleo‐latitude, while a humid climate was supported by palaeobotanic assemblages in East Asia. Here, we report the occurrence of massive primary lacustrine dolomite and magnesite in the central East Asia during the middle Eocene. We provide a novel perspective from magnesium isotopes to link the formation of Mg‐carbonates to seasonal dry‐wet cycles. Rapid magnesium input during the rainy season and intense evaporation in the dry season likely caused the formation of magnesium carbonates in an enclosed lake. These findings provide insights into hydroclimatic seasonality during the Eocene, contributing to our understanding of the hydrological cycle response to a greenhouse climate.

Spatiotemporal coupling analysis of surface water and groundwater in Tibet based on multi-source sensors

Abstract. Lakes and groundwater are two crucial components of the global terrestrial water cycle, collectively forming a vital network for Earth's water resources. However, in the Tibetan region, the spatiotemporal relationship between lakes and groundwater and their impact on the local hydrological cycle remain inadequately understood. Satellite remote sensing serves as an effective observational tool, enabling comprehensive investigation and analysis of surface lakes and groundwater in Tibet with high spatial resolution. Therefore, this study integrates Landsat and Cryosat-2 satellite data to examine the spatiotemporal patterns of surface lake extents and water levels in Tibet. Additionally, combining Gravity Recovery and Climate Experiment (GRACE) satellite observations with the Global Land Data Assimilation System (GLDAS) model data, we quantitatively analyze the spatiotemporal variations in groundwater storage and its correlation with lake water. The results indicate that: 1) Rivers and lakes in Tibet are mainly located in the central and northwest regions, displaying noticeable intra-annual variations; 2) Substantial lagged relationships exist between groundwater storage and lake water levels and areas, revealing that lakes contribute significantly to groundwater replenishment, especially in the Ngari prefecture and Lhokha prefecture. This study comprehensively utilizes multi-source remote sensing data to dynamically monitor surface and groundwater in Tibet, providing robust support for a better understanding of the interaction between groundwater and surface water.

Asymmetric responses of summer soil moisture anomalies to the large-scale teleconnections on the Loess Plateau between 2000 and 2020

Soil moisture is a key regulator of hydrological cycle and is closely related to vegetation growth and climate changes, which is mainly replenished by summer precipitation on the Loess Plateau. However, the response of soil moisture content (SMC) anomalies during summer on the Loess Plateau to large-scale teleconnection remains unclear. Here, using the empirical orthogonal function (EOF) method, this study extracted a homogenized area with significant variability of normalized difference vegetation index (NDVI) (p<0.01), which was called sensitive areas for vegetation restoration (SAVR) of the Loess Plateau. Based on 1 km daily soil moisture dataset named SMCI1.0 at top 1 m, we demonstrated that there was an interannual fluctuation of summer SMC from 2000 to 2020 over the SAVR of the Loess Plateau. Spatially, SMC during summer in the SAVR of the Loess Plateau exhibited an enhanced regional difference characterized by ‘dry to drier and wet to wetter’. Importantly, abnormal SMC during summer in the SAVR of the Loess Plateau can been attributed to distinct circulation pattern and anomalous water vapor transport, which showed asymmetrical distributions between positive and negative anomalous years of summer SMC. Due to the activities of western Pacific subtropical high (WPSH) and low-pressure system around the Lake Baikal (an anomalous anticyclone prevailed over the western north Pacific), the positive (negative) anomalous years of summer SMC witnessed net water vapor influx (outflux) anomalies to the Loess Plateau compared to the climatology, corresponding to anomalous upward (sinking) motions, further leading to more (less) SMC in summer over the SAVR of the Loess Plateau, respectively. The conclusions of this study have implications for excavating early warning information of SMC anomalies and natural restoration sustainable management on the Loess Plateau.

Dynamics of dissolved inorganic carbon (DIC) and stable C isotope ratios (δ13CDIC) in a tropical watershed with diversified land use in São Paulo State, Brazil

The fluvial transport of dissolved inorganic carbon (DIC) is an important component of the global carbon cycle. Herein, we assessed the dynamics of DIC and the C stable isotopic composition (δ13CDIC) in a watershed with diversified land use in São Paulo State (Brazil), more specifically in the Sorocaba River basin (SRB) and considered the temporal and spatial scales. For this purpose, twelve fluvial samples at each sampling point (e.g., S1, S2, S3, S4 and S5) were collected in the SRB, from June 2009 to May 2010, which represented one complete hydrological cycle that included the extremes of the rainfall and discharge regimes. In addition, the δ13CDIC values were also characterized in the wet and dry season at all sampling points to verify their seasonal variability. The results reflected the seasonal variation in discharges, water temperatures, and electrical conductivities. Most of the DIC was transported in the wet season at all sampling points, where the less negative δ13CDIC values were characterized. The natural sources of DIC are associated with atmospheric/soil CO2 consumption. The anthropogenic impacts on both [DIC] and δ13CDIC are linked to untreated urban sewage that is discharged directly into the Sorocaba River, as well as to aquatic photosynthesis in the Itupararanga Reservoir. From 1970 to 2020, the modeling proposed in this study indicated that the annual flux of DIC (Friver) varied from 9.0 to 78.7 t km−2 a−1, confirming that the El Niño Southern Oscillation (ENSO) controlled Friver in the SRB, with higher and lower Friver values occurring during strong El Niño (EN) and La Niña (LN) years. The average Friver value was 20 t km−2 a−1, which is higher than those obtained in natural several temperate and tropical watersheds due to the influences of urban areas on [DIC] in the SRB.

Escalating rainstorm-induced flood risks in the Yellow River Basin, China

The warming climate-induced intensification of hydrological cycle is amplifying extreme precipitation and increasing flood risk at regional and global scales. The evaluation of flood risk, which depends on assessment indicators, weights, as well as data quality, is the first step toward mitigation flood disasters. In this study, we accepted ten risk assessment indicators concerning hazard of disaster-causing factors, sensitivity of hazard-forming environments, and vulnerability of disaster-bearing bodies. We used a combined weighting method based on the analytic hierarchy process and entropy weight (AHP-EW) technique to evaluate rainstorm-induced flood risks across the Yellow River Basin (YRB) from 2000 to 2018. We observed flood hazards are intensifying across the YRB. Specifically, areas with medium flood hazards expanded from the lower to the middle and upper YRB. The sensitivity to floods exhibited a spatial pattern of increasing from southeast to northwest (lower to upper YRB). The increase in vegetation coverage in the middle and upper reaches of the YRB reduces the sensitivity to flood disasters. Flood vulnerability shows an increasing trend, with higher vulnerability mainly observed in the middle and lower YRB. The overall flood risk in the YRB shows an increasing trend, with a 9-fold increase in flood risk from 2000 to 2018. Medium to high flood risk and vulnerability can mainly be identified in the middle and lower YRB, where population and gross domestic product are concentrated. The intensifying rainstorm-induced flood risks over urban areas in these regions should arouse public concern.

Effects of reduced snowpack due to climate warming on abiotic and biotic soil properties in alpine and boreal forest systems

Reduction in snow cover, depth, onset, and duration of seasonal snow in mid-latitude regions due to climate warming has multiple global and local scale ecosystem impacts. These effects include modulations of the hydrological cycles and increases in land surface solar radiation absorption due to decreased albedo. Changes in snow cover characteristics also affect underlying soils. Snow has an insulating effect on soils by decoupling air and soil temperatures, thus seasonal snow cover reduction leads to overall lower soil temperatures and an increase in freeze-thaw cycles. This is especially prominent during the fall and spring thaw seasons when the snow cover is not as extensive. This in turn has downstream impacts on soil physical, chemical, and biological properties. Among these impacts are soil moisture reduction, temperature, frost regimes, soil pH shifts, and alteration in nutrient flux dynamics during winter, snowmelt period and the following summer growing season. These changes in soil physicochemical properties due to snowpack reduction can then impact the biological soil properties via increased plant root mortality, reduced abundance and diversity of soil arthropods, and shifts in composition, abundance and activity of soil microbial communities. All these soil biotic factors can in turn alter the dynamics of soil nutrient fluxes and future greenhouse gas emissions. Here, we integrate data on the effects of snow cover reduction on abiotic and biotic soil properties, with focus on temperate alpine and forest ecosystems and with an outlook on future impacts.

Hydrological Analysis of Agricultural Reservoir Watersheds Based on Water Utilization System Using the Catchment Hydrology Cycle Analysis Tool Model

In this study, the catchment hydrology cycle analysis tool (CAT) model was used to conduct a comprehensive hydrological analysis of the water balance of agricultural reservoirs. Data from 2010 to 2017, including precipitation, water level data in the reservoir, groundwater usage, and wastewater discharge, were collected and compiled for the upper reaches of the Hantan River Dam. The current conditions and content curves of the 11 reservoirs within the watershed were investigated and recorded. The results were analyzed by simulating three scenarios: treating the entire watershed as 1 unit, dividing the watershed into 5 sub-watersheds according to the standard watershed criteria, and further subdividing it into 27 watersheds, taking into account the presence of agricultural reservoirs. In cases where watershed information is lacking, it is deemed that subdividing the watershed can enhance efficiency. The highest model efficiency was observed in the 27 sub-basins, particularly when accounting for agricultural reservoirs. This study proposed an efficient method for hydrological analysis of watersheds including ungauged areas.

A warming-induced glacier reduction causes lower streamflow in the upper Tarim River Basin

Study areaThree headwater basins of the Tarim River Study focusThis study built upon existing knowledge by incorporating threshold melting temperatures into the Spatial Processes in Hydrology (SPHY) model and decomposing the streamflow changes into individual runoff components. Additional glacier retreat rate data were used to calibrate the improved SPHY, which provides better constrained estimates of glacier response to climate change. We employed bias-corrected simulations from Coupled Model Intercomparison Project Phase 6 (CMIP6) models to drive the improved SPHY under four future scenarios (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5). New hydrological insights for the regionModeling results show accelerated glacier melt in the future, with glacier volume at the end of this century projected to be less than 20% of the current level under SSP5–8.5. Furthermore, future streamflow is expected to decrease, most notably in the Karakash River basin under the SSP1–2.6 scenario. The reduction in streamflow, mainly during the summer months, results from decreased glacier melt runoff, which cannot be offset by increased rainfall runoff. Additionally, the implementation of climate change mitigation measures could delay glacier loss, but the dominant component of runoff would still shift from current glacier melt to future rainfall. Plain language summaryGlobal warming accelerates the hydrological cycle, altering the temporal and spatial patterns of streamflow, especially in cold regions, such as the Tarim River Basin. Understanding future streamflow changes is important for the economic development and ecological protection of this region, which will help to manage the risk of water shortages and to plan engineering works to mitigate water shortage crises. We therefore used state-of-the-art climate simulation to project future streamflow changes over three basins of the Upper Tarim River. We found that under all future scenarios, runoff will decrease in these basins. This decrease is mainly due to glacier retreat and cannot be mitigated by anticipated increases in rainfall in the future.

The Source-to-Sea Landscape: A hybrid integrative territory management approach

Whether fresh or salty, water is a unique resource, a continuum interlinked by the hydrological cycle. It forms a complex system connected to the landscape. When the landscape is altered, water flows and their benefits are impacted. Degraded land compromises water resources. The governance and management of landscape and water resources are handled in a fragmented manner and in separate contexts. The Source-to-Sea approach offers an integrative vision based on systems thinking that focuses its concerns on the interaction among parts, flows, and processes. It proposes a framework for the governance and management of freshwater and marine water but does not bring the landscape into the context of the approach. This research used an analytical-deductive method to explore the interactions and connections between the Source-to-sea approach, landscape concepts and approaches, and the guidelines of the European Landscape Convention. The main objective was to identify and assess the feasibility of integrating these elements. The integration resulted in a governance and management approach termed the S2S Landscape approach. It is grounded in systems thinking, practical learning, active participation, and adaptive governance and management, providing an integrated vision between landscape and water. The approach includes four essential steps (Comprehension, Involvement, Planning, and Execution and Monitoring) that address the complex connections that freshwater and marine water maintain in the landscape, considering physical, biological, socio-environmental, and economic aspects across all segments, from the land to the open sea. This S2S Landscape approach may be the path to address the challenges of governance and sustainable management of resources in an interconnected and constantly changing world.

Changes in Mesoscale Convective System Precipitation Structures in Response to a Warming Climate

AbstractMesoscale convective systems (MCSs) are crucial components of the hydrological cycle and often produce flash floods. Given their impact, it is important to understand how they will change under a warming climate. This study uses a satellite‐ and radar‐based MCS tracking algorithm on convection‐permitting climate model simulations and examines changes in MCS properties and precipitation structures between historical and future simulations. An underestimation in MCS total precipitation is evident in historical simulation compared to observations, due to model's depiction of MCS precipitation area and summertime occurrence frequency. Under pseudo‐global warming, increases in MCS frequency and total warm season precipitation are observed, most notably in the southern U.S. The precipitation intensity and precipitating area generated by future MCSs also rises and results in an increase in precipitation volume. MCS precipitation structures are further classified into convective core and stratiform regions to understand how change in these structures contributes to future rainfall changes. In a warmer climate, the stratiform region demonstrates minimal change in size, but increases in mean precipitation rate and mean maximum precipitation rate by 15% and 29% are noted, respectively. A more robust future response is observed in the convective core region, with its size, mean precipitation rate and mean maximum precipitation rate increasing significantly by 24%, 37% and 42%, respectively. Finally, by examining the environmental properties of MCS initial condition, future intensification of convective rain may be attributed to a combined effect of substantial increases in atmospheric instability and moisture availability.