Search Results (396)

Given that the Sunkoshi River watershed (located in the southern foot of the Himalayas) is sensitive to climate change and its mountain ecosystem provides important services, we aim to evaluate its spatial and temporal variation patterns of vegetation, represented by the Normalized Difference Vegetation Index (NDVI), during 2000–2021 and identify the dominant driving factors of vegetation change. Based on the NDVI dataset (MOD13A1), we used the simple linear trend model, seasonal and trend decomposition using loess (STL) method, and Mann–Kendall test to investigate the spatiotemporal variation features of NDVI during 2000–2021 on multiple scales (annual, seasonal, monthly). We used the partial correlation coefficient (PCC) to quantify the response of the NDVI to land surface temperature (LST), precipitation, humidity, and soil moisture. The results indicate that the annual NDVI in 52.6% of the study area (with elevation of 1–3 km) increased significantly, while 0.9% of the study area (due to urbanization) degraded significantly during 2000–2021. Daytime LST dominates NDVI changes on spring, summer, and winter scales, while precipitation, soil moisture, and nighttime LST are the primary impact factors on annual NDVI changes. After removing the influence of soil moisture, the contributions of climate factors to NDVI change are enhanced. Precipitation shows a 3-month lag effect and a 5-month cumulative effect on the NDVI; both daytime LST and soil moisture have a 4-month lag effect on the NDVI; and humidity exhibits a 2-month cumulative effect on the NDVI. Overall, the study area turned green during 2000–2021. The dominant driving factors of NDVI change may vary on different time scales. The findings will be beneficial for climate change impact assessment on the regional eco-environment, and for integrated watershed management. Full article

Non-Newtonian debris flows represent a critical challenge for hydraulic infrastructure in mountainous regions, often causing significant damage and service disruption. However, current models typically simplify these flows as Newtonian, leading to inaccurate design assumptions. This study addresses this gap by comparing the hydraulic behavior of Newtonian and non-Newtonian flows in an alluvial fan, using the Amoray Gully in Apurímac, Peru, as a case study. This gully intersects the Interoceánica Sur national highway via a low-water crossing (baden), making it a relevant site for evaluating debris flow impacts on critical road infrastructure. The methodology integrates hydrological analysis, rheological characterization, and hydraulic modeling. QGIS 3.16 was used for watershed delineation and extraction of physiographic parameters, while a high-resolution topographic survey was conducted using an RTK drone. Rainfall-runoff modeling was performed in HEC-HMS 4.7 using 25 years of precipitation data, and hydraulic simulations were executed in HEC-RAS 6.6, incorporating rheological parameters and calibrated with the footprint of a historical event (5-year return period). Results show that traditional Newtonian models underestimate flow depth by 17% and overestimate velocity by 54%, primarily due to unaccounted particle-collision effects. Based on these findings, a multi-barrel circular culvert was designed to improve debris flow management. This study provides a replicable modeling framework for debris-prone watersheds and contributes to improving design standards in complex terrain. The proposed methodology and findings offer practical guidance for hydraulic design in mountainous terrain affected by debris flows, especially where infrastructure intersects active alluvial fans. Full article

Phewa Lake, Nepal’s second-largest natural lake, is under increasing ecological stress due to sedimentation, shoreline encroachment, and water quality decline driven by rapid urban growth, fragile mountainous catchments, and changing climate patterns. This study employs an integrated approach combining sediment yield estimation from its catchment using RUSLE, shoreline encroachment analysis via satellite imagery and historical records, and identification of pollution sources and socio-economic factors through field surveys and community consultations. The results show that steep, sparsely vegetated slopes are the primary sediment sources, with Harpan Khola (a tributary of Phewa Lake) contributing over 80% of the estimated 339,118 tons of annual sediment inflow. From 1962 to 2024, the lake has lost approximately 5.62 sq. km of surface area, primarily due to a combination of sediment deposition and human encroachment. Pollution from untreated sewage, urban runoff, and invasive aquatic weeds further degrades water quality and threatens biodiversity. Based on the findings, this study proposes a way forward to mitigate sedimentation, encroachment, and pollution, along with a sustainable revitalization plan. The approach of this study, along with the proposed sustainability measures, can be replicated in other lake systems within Nepal and in similar watersheds elsewhere. Full article

Sediment fingerprinting was utilized to identify potential hotspots of soil erosion and sediment transport pathways in the Nile Nyabarongo Upper Catchment (NNYU) in Rwanda, where rivers and reservoirs are suffering from alarmingly high levels of sedimentation. Sediment fingerprinting is a practical approach used to identify erosional hotspots and sediment transport processes in highly mountainous regions undergoing swift land use transformation. This technique involves a statistical comparison of the elemental composition of suspended sediments in river water with the elemental composition of soils belonging to different geological formations present in the catchment, thereby determining the sources of the suspended sediment. Suspended sediments were sampled five times over dry and wet seasons in all major headwater tributaries, as well as the main river channel, and compared with soils from respective delineated watersheds. Elemental composition was obtained using laser ablation inductively coupled plasma mass spectrometry, and elements were chosen that could reliably distinguish between the various geological types. The final results indicate different levels of sediment contribution from different geological types. A three-level intervention priority system was devised, with Level 1 indicating the areas with the most serious erosion. Potential sources were located on an administrative map, with the highest likely erosion over the study period (Level 1) occurring in Kabuga cell in the Mwogo sub-catchment, Nganzo and Nyamirama cells in the Nyagako sub-catchment and Kanyana cell in the NNYU downstream sub-catchment. This map enables the pinpointing of site visits in an extensive and rugged terrain to verify the areas and causes of erosion and the pathways of sediment transport. Sediment concentrations (mg L⁻¹) were the highest in the Secoko and Satinsyi tributaries. The composition of suspended sediment was seen to be temporally and spatially dynamic at each sampling point, suggesting the need for an adequate number of sampling locations to identify erosion hotspots in a large mountainous watershed. Apart from prioritizing rehabilitation locations, the detailed understanding of critical zone soil–land cover–climate processes is an important input for developing region-specific watershed management and policy guidelines. Full article

In this review paper, we perform a comprehensive review of the current state of the art, worldwide applications, and modifications of the Snowmelt Runoff Model (SRM). Snow is a significant element of the hydrologic cycle and is sometimes regarded as the primary source of streamflow in watersheds at high latitudes and altitudes. Quantitative assessment of snowmelt runoff is crucial for real-world applications, including runoff projections, reservoir management, hydro-electricity production, irrigation techniques, and flood control, among others. Numerous hydrological modeling software have been developed to simulate snowmelt-derived streamflow. The SRM is one of the well-known modeling software developed to simulate snowmelt-derived streamflow. The SRM simulates snowmelt runoff with fewer data requirements and uses remotely sensed snow cover extent. This makes the SRM appropriate for use in data-scarce locations, particularly in remote and inaccessible mountain watersheds at higher elevations. It is a conceptual, deterministic, semi-distributed, and degree-day hydrological model that can be applied in mountainous basins of nearly any size. Recent advancements in remote sensing integration and climate model coupling have significantly enhanced the model’s ability to estimate snowmelt runoff. Additionally, numerous studies have recently improved the traditional SRM, further enhancing its capabilities. This paper highlights some of the global SRM research, focusing on the working of the model, input parameters, remote sensing data availability, and modifications to the original model. Full article

Flash flood disasters occur frequently under the influence of climate change and human activities, with the characteristics of strong suddenness, a wide range of hazards, and difficult prediction. Obtaining high-spatial- and high-temporal-resolution and high-precision rainfall monitoring and forecasting data is of great significance for accurate early warnings for flash flood disasters. In order to evaluate the advantages of X-band radar inverted rainfall in flash flood simulations, two typical flood events (3 July 2024 and 13 July 2024) in the Guangrun River Basin were studied. A comparative study between X-band radar inversion-based rainfall and rainfall measured at rainfall stations in terms of the flooding process and inundation extent was carried out using the China Flash Flood Hydrological Model (CNFF) and the two-dimensional hydrodynamic model (FASFLOOD). The results indicated that the temporal and spatial distribution characteristics of rainfall inversion by X-band radar were highly consistent with the measured rainfall at rainfall stations; in terms of simulating flood processes, rainfall based on X-band radar inversion performed better in key indicators such as the relative error of runoff depth, relative error of peak flow, error in time of peak occurrence, and Nash–Sutcliffe efficiency coefficient (NSE). In terms of simulating flood inundation, the simulation results based on X-band radar inversion and the measured rainfall from rainfall stations were consistent in the trend of rising and falling water processes and inundation range changes, and X-band radar could more accurately capture the spatial heterogeneity of rainfall. This study can provide technical support for disaster prevention and reductions in mountain floods in small watersheds. Full article

The reduction in and irregularity of spring precipitation in Iberian latitudes over the past few decades are well-documented. This study analyses the behaviour of the accumulated series of monthly and annual spring precipitation for a broad section of the central-eastern part of the peninsula between Plasencia (Western Central System) and the south-eastern part of the Iberian System over the past 70 years. The area was chosen in accordance with the layout of the mountain systems and watersheds that cross the Iberian Peninsula from the west to east. Ten-year series and trends in the precipitation values accumulated between 1951 and 2020 provided by the AEMET were analysed together with their relationship with the pressure values for the same dates modelled by the Copernicus Climate Change Service. The totals obtained show an increasing weight regarding spring precipitation for the eastern sector (40–44%) and a gradual reduction in the west (30%). These percentages show the positive trend of the ten-year values for the easternmost sector. Spring precipitation increases are observed in the easternmost areas (7 mm/decade), while the central and western sectors generally show declining values (−35 mm/decade). The atmospheric pressure at height (Z500) and surface level (Z1000) were analysed together with their relationship with accumulated precipitation, revealing a clear trend of a dominance of high pressures in Z500. Full article

The assessment of the maximum snow-water equivalent in mountains is important for understanding the mechanism of their formation, as well as for hydrological calculations. The low density of the observation network and the high complexity of ground-based snow-measuring operations have led to the widespread use of remote methods to obtain such data. In this study, the maximum water reserve of the Uba River basin was calculated for the period of 2020–2023, based on data from the Sentinel-2 satellite regarding the position of the seasonal snow line, obtained using the temperature-based melt-index method. This study determined the snowmelt coefficients for the meteorological stations at Zmeinogorsk, Shemonaikha, and Ridder. Maps were constructed to show the distribution of the maximum snow-water equivalent in the Uba River basin. The spatial differentiation features of the snow cover were revealed, depending on the elevation, slope exposure, and distance from the watersheds. It was established that the altitudinal distribution of snow cover on the northern and southern macro-slopes of the ridges is asymmetric: in the western part of the basin, within the elevation range of 500–1200 m, the maximum water reserves of snow cover are greater on the southern slopes, but they become higher on the northern slopes above 1200 m. In the eastern part of the basin, they are always larger on the northern slopes. The greatest differences in the distribution of snow cover between the slopes occur near the watersheds. Full article

Vegetation restoration in seismically active regions involves complex interactions between geological hazards and ecological processes. Understanding the spatiotemporal patterns of vegetation recovery is critical for assessing disaster evolution, evaluating mitigation effectiveness, and guiding ecological resilience planning. This study investigates post-earthquake vegetation dynamics in the Chutou Gully watershed, located in the 12 May 2008 Wenchuan earthquake zone, using NDVI data from 2000 to 2022. Results reveal a sharp decline in vegetation cover following the earthquake, followed by a steady recovery trend, with NDVI values projected to return to pre-earthquake levels by 2030. Degradation was concentrated in debris flow channels, while more stable adjacent slopes exhibited stronger recovery. Over time, the area of poorly restored vegetation significantly declined, indicating increased ecosystem resilience. The findings highlight the need for site-specific ecological restoration strategies tailored to localized recovery conditions. This study provides valuable insights for disaster mitigation agencies, ecological planners, and local governments working in mountainous hazard-prone regions, and contributes to the long-term sustainability of ecosystems in disaster-prone areas. Full article

Nepal is known for its complex terrain, climate, and vegetation dynamics, resulting in tremendous hydrologic variability and complexity. Accurately quantifying the water balances at the national level in Nepal is extremely challenging and is currently not available. This study constructed long-term (2000–2022) water balances for 358 watersheds across Nepal by integrating watershed hydrometeorological monitoring data, remote sensing products including Leaf Area Index and land use and land cover data, with an existing ecohydrological model, Water Supply Stress Index (WaSSI). The WaSSI model’s performance is assessed at both watershed and national levels using observed water yield (Q) and evapotranspiration (ET) products derived from remote sensing (ETMonitor, PEW, SSEBop) and eddy flux network (i.e., FLUXCOM). We show that the WaSSI model captured the seasonal dynamics of ET and Q, providing new insights about climatic controls on ET and Q across Nepal. At the national scale, the simulated long-term (2000–2020) mean annual Q and ET was about half of the precipitation (1567 mm), but both Q and ET varied tremendously in space and time as influenced by a monsoon climate and mountainous terrain. We found that watersheds in the central Gandaki River basin had the highest Q (up to 1600 mm yr⁻¹) and ET (up to 1000 mm yr⁻¹). This study offers a validated ecohydrological modeling tool for the Himalaya region and a national benchmark dataset of the water balances for Nepal. These products are useful for quantitative assessment of ecosystem services and science-based watershed management at the national scale. Future studies are needed to improve the WaSSI model and remote sensing ET products by conducting ecohydrological research on key hydrologic processes (i.e., forest ET, streamflow generations of small watersheds) across physiographic gradients to better answer emerging questions about the impacts of environmental change in Nepal. Full article

Polychlorinated biphenyls (PCBs) are classified as persistent organic pollutants (POPs) due to their potential threat to both ecosystems and human health. The Tibetan Plateau (TP), characterized by its low temperatures, pristine ecological conditions, and remoteness from anthropogenic influences, serves as the investigation region. This study analyzed water samples from the temperature glacial watershed and employed the risk assessment method established by the United States Environmental Protection Agency (US EPA) to assess both carcinogenic and non-carcinogenic risks of PCBs in five age groups. The total concentrations of PCBs (∑₃PCBs) varied from 738 to 1914 ng/L, with a mean value of 1058 ng/L, which was comparable to or exceeded levels reported in the surface water around the TP. Notably, the riverine sites located near the villages and towns exhibited the highest pollution levels. Our analyses indicated that glacier melting, long-range atmospheric transport (LRAT), reductive dechlorination processes, and various anthropogenic activities might be potential sources of PCB emission in the Meili Snow Mountains. According to the established national and international water quality standards, as well as toxic equivalency concentrations (TEQs) for dioxin-like PCBs (DL PCBs), the PCB concentrations detected in this study could result in serious biological damage and adverse ecological toxicological effects. However, the PCBs in all samples posed a negligible cancer risk to five age groups, and a non-carcinogenic risk to adults. These findings contribute valuable insights into the risks and sources of PCBs and may serve as a foundational reference for subsequent study of these compounds in the Meili Snow Mountains area of the southeastern TP. Full article

Accurate runoff forecasting is crucial for disaster prevention and mitigation, as well as water resource allocation planning. However, the accuracy of runoff forecasting in high mountain watersheds is limited by the complexity of terrain and the scarcity of observation data. In recent years, machine learning models have been widely used for runoff prediction. In order to explore the application effect of the Long Short-Term Memory (LSTM) network in high mountain watersheds, this paper takes the Nyang River Basin (NRB) in a typical watershed on the Qinghai–Tibet Plateau (QTP) as the research object, and uses LSTM models to study the impact of different input variable combinations on runoff prediction under multiple prediction periods. The results indicate that with the extension of the forecast period, the impact of historical runoff on runoff prediction accuracy gradually decreases, while the impact of precipitation and temperature on runoff prediction accuracy gradually increases. When the forecast period exceeds 13 days, the contribution of precipitation increases more significantly. The use of historical runoff and forecasting that includes historical runoff and precipitation yields the most robust results, with good forecasting performance within 25 days of the forecast period. Moreover, the larger the watershed area, the better the runoff forecasting effect. Full article

Mountain watersheds play a crucial role in sustaining freshwater resources, yet they are highly vulnerable to climate change. In this study, we investigated the summer water temperature of 35 alpine springs in the highest part of the Retezat Mountains, Southern Carpathians, between 2020 and 2023. During the four-year monitoring period, water temperatures across all springs ranged from 1.2 °C to 10.5 °C. Springs emerging from rock glaciers had the lowest average temperature (2.37 °C), while those on cirque and valley floors were the warmest (6.20 °C), followed closely by springs from meadow-covered slopes (6.20 °C) and those from scree and talus slopes (4.70 °C). However, only four springs recorded summer temperatures below 2 °C, suggesting a direct interaction with ground ice. The majority of springs exhibited temperatures between 2 and 4 °C, exceeding conventional thresholds for permafrost presence. This challenges the applicability of traditional thermal indicators in marginal periglacial environments, where reduced ground ice content within rock glaciers and talus slopes can lead to spring water temperatures ranging from 2 °C to 4 °C during summer. Additionally, cold springs emerging from rock glaciers displayed minimal daily and seasonal temperature fluctuations, highlighting their thermal stability and decoupling from atmospheric conditions. These findings underscore the critical role of rock glaciers in maintaining alpine spring temperatures and acting as refugia for cold-adapted organisms. As climate change accelerates permafrost degradation, these ecosystems face increasing threats, with potential consequences for biodiversity and hydrological stability. This study emphasizes the need for long-term monitoring and expanded investigations into water chemistry and discharge dynamics to improve our understanding of high-altitude hydrological systems. Furthermore, it provides valuable insights for the sustainable management of water resources in Retezat National Park, advocating for conservation strategies to mitigate the impacts of climate change on mountain hydrology and biodiversity. Full article

Mountain forestscapes are among the planet’s most vital socio-ecological systems, functioning as critical reservoirs of biodiversity, regulators of climate, and essential sources of water and livelihood for surrounding and downstream communities. However, these landscapes face intensifying threats from climate change, land-use transformation, resource extraction, unsustainable tourism, and fragmented governance. While sustainable forest management has provided essential frameworks for conservation, its focus on maintaining existing conditions is increasingly insufficient amid accelerating ecological and social decline. This paper explores the conceptual and practical evolution from sustainability to regeneration in mountain forest management, distinguishing between the theoretical foundations of each paradigm and analyzing the key drivers of degradation across diverse biocultural regions. Methodologically, the study employs a transdisciplinary and qualitative design, integrating critical literature synthesis, comparative regional analysis, and Indigenous and local knowledge systems. A structured review of 72 peer-reviewed sources and ethnographic materials was conducted, combined with a qualitative comparative analysis (QCA) of mountain case studies from the Alps, Carpathians, Andes, Eastern Arc Mountains, and Himalayas. The study synthesizes regenerative strategies such as ecological connectivity restoration, agroecological landscape design, participatory watershed management, and adaptive, polycentric governance. Based on these insights, an integrated framework for regenerative mountain forestscape management is proposed, aligned with global policy agendas including the UN Decade on Ecosystem Restoration, nature-based solutions (NbS), and the post-2020 Global Biodiversity Framework. By prioritizing ecological renewal, cultural continuity, and community agency, this work contributes to transformative, place-based approaches that restore the functionality, resilience, and integrity of mountain landscapes. Full article

Tree ring chronologies (tree ring width—TRW, earlywood—EW, latewood—LW) were constructed to investigate fir’s (Abies borisii-regis Mattf.) response to key hydrometeorological factors, namely precipitation, temperature and drought (12-month Standardized Precipitation Evapotranspiration Index, SPEI-12). There has been only one previously published study conducted in the northern area of the species’ expansion (Albania). The current study was conducted in the southern area of the species’ expansion (Central Greece). Precipitation was the most important factor that affected tree growth. May precipitation was positively correlated with LW, while June and July precipitation was positively correlated with both EW and LW. Previous September precipitation was positively correlated with EW and LW. Interestingly, the current September precipitation was negatively correlated with EW. High temperatures in April showed a positive relation with LW, high temperatures in June negatively affected all chronologies, while high temperatures July and August were negatively related with LW. High autumn temperatures in the previous year significantly (negatively) influenced all tree ring chronologies. The SPEI index revealed that wet conditions during May and June positively correlated with high tree growth for both EW and LW, while wet conditions in July and August significantly affect LW formation. Wet conditions in the previous September also had a positive effect on tree growth. SPEI showed similar behavior with precipitation, showing that precipitation is the driving factor in fir growth. The results highlight the importance of summer rainfall and temperature in controlling tree growth in Mediterranean regions. The study revealed significant knowledge on the susceptibility of Abies borisii-regis Mattf. to climate variability and highlighted its consequences for future forest management plans. Full article