Soil erosion is one of the global threats to the environment. Further, climate and vegetation changes have pronounced effects on soil erosion in high-mountain areas. In this study, the revised universal soil loss equation (RUSLE) was improved by developing a method for calculating snowmelt runoff erosivity based on a simulated snowmelt runoff and the observed sediment load, using which the soil erosion rate in the upper Heihe River Basin (UHRB) was calculated. The proposed approach provides an effective method for estimating the soil erosion rate and identifying the causes for its change in high-mountain areas. The normalized difference vegetation index (NDVI) was significantly and positively correlated with both precipitation and temperature in the region and exhibited a significant increasing trend. The increase in NDVI led to a decrease in the soil erosion rate (for the annual, rainfall, and snowmelt periods), although erosive rainfall and snowmelt runoff showed increasing trends, indicating the dominating impact of vegetation cover on soil erosion. The average soil erosion rate of UHRB was 806.2 t km⁻² a⁻¹ from 1982 to 2015. On average, soil erosion during rainfall and snowmelt periods contributed to 90.67% and 9.33% of annual soil erosion, respectively. However, the resultant soil erosion rate caused by 1 mm of snowmelt runoff was about 1.9 times that caused by 1 mm erosive rainfall. Soil erosion during the snowmelt period was particularly sensitive to temperature and showed consistent responses to climate and vegetation changes in UHRB and its two tributaries. An increasing NDVI promoted by climate change and anthropogenic factors played a major role in alleviating soil erosion, and the warming exerted intense impacts on soil erosion during the snowmelt period. These findings would be helpful for proposing effective measures for soil conservation in high-mountain areas under climate and vegetation changes.

Groundwater is the most unexplored element of the hydrologic cycle on the Tibetan Plateau (TP) due to harsh climate conditions. This study aims at delineating and characterizing the unexplored Zhanongtang–Ganmanong aquifer, situated in the Zhagu subcatchment of the Nam Co catchment, south-central TP. Multiple hydrogeophysical and lithological in situ field and laboratory methods are applied: depth-to-water-table measurements, grain size analysis, hydraulic empirical and field methods to estimate hydraulic conductivity (K), and analysis of electrical resistivity tomography profiles. Integration of these methods revealed the existence of a Quaternary hydrostratigraphic unit that was found to be unconsolidated, laterally heterogeneous and homogeneous over depth. The results revealed consistent K ranges of three K zones, which is in accordance with local lithology. The K ranges are applicable to other locations within the Nam Co catchment with similar lithology as in the study area without further field experiments. Permafrost was found to be absent in the study area ranging from 4730 m a.s.l. to 5200 m a.s.l. altitude. These results provide insight into the hydrogeological conditions of the TP and are useful for conceptual and numerical groundwater flow modeling to predict future changes of water fluxes and water budgets caused by climatic change, especially in remote areas.

Alpine lakes on the Tibetan Plateau have significantly changed under a changing climate over past decades. However, the changing patterns of the inflow sources of the lakes, i.e., rainfall and the melt water of snow and glaciers, and their response to climate change remain uncertain because obtaining accurate precipitation and melt water discharge is difficult due to the complex topography, spatial variability, and scarce stations of the alpine area. A distributed hydrological model, J2000, was employed in this study to simulate runoff component variations of the Yamzho Yumco Lake glaciated basin during 1974–2019. Except for observed daily runoff from two tributaries, a High Asia Refined (HAR) high-resolution reanalysis of precipitation data was combined with field precipitation gradient observation and snow cover area validation, all performed simultaneously to reduce the uncertainty of inflow components in the model. Results showed that the average runoff into the lake during 1974–2019 was 5.5 ± 1.4 × 10⁸ m³/10a, whereas rainfall runoff, glacier melt runoff, snowmelt runoff, and baseflow contributed to 54.6%, 10.8%, 1.8%, and 32.7% of total runoff in mean, respectively. Seasonal runoff in spring, summer, autumn, and winter accounted for 6.7%, 60.6%, 23.9% and 8.8% of annual total runoff, respectively. In glacial areas, the reduction in total runoff after removing the precipitation trend was 1.4 times than that of temperature, and in non-glacial areas, the reduction in total runoff after removing the precipitation trend was 1.6 times than the increase in total runoff after removing the temperature trend. The proportion of rainfall runoff increased at a rate of 1.0%/10a, whereas the proportion of melt runoff decreased at a rate of 0.07%/10a during the study period.

Temperature lapse rate (TLR) is an important parameter for simulations of snow/glacier melts in alpine watersheds. However, the traditional scheme estimates TLR mainly based on a limited number of stations and may not be suitable for alpine watersheds with scarce observations. To overcome this problem, this study developed a new basin-oriented TLR scheme based on Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature data which was applied in a typical glacierized watershed on the northern slope of the Himalayas. The new TLR scheme was evaluated by comparison with the station-based traditional TLR scheme in terms of performance in simulations of both snow cover area and runoff using the same hydrological model. The results showed that the monthly TLRs estimated by the new scheme presented a more reasonable seasonal pattern than those estimated by the traditional scheme. The model using the new TLR scheme showed better performance in discharge simulations of low-runoff months than that using the traditional TLR scheme. The R-squared value of multiyear mean monthly snow cover area of the former (0.82) was also higher than that of the latter (0.56). This study provides an efficient framework for estimating TLR based on remote sensing for alpine watersheds with scarce observations.

The aquifers on the Tibetan Plateau (TP) constitute as origin for major river systems, which are supplying millions of people all over Asia. Increasing population and tourism activities leading to larger water consumption. Hence, water supply is getting increasingly important. The TP is a sensitive system and is noticeable reacting climate change. Past decades are marked with, increasing trends of precipitation, melting of glaciers and degradation of permafrost and have generally lead to rising water levels in lakes on the TP. To ensure future water supply, aquifer characterisation and future prognosis on groundwater behavior are therefore necessary. However, due to the remote character of the TP, knowledge according to hydrogeological parameter is scarce. The aim of this study is therefore to estimate a range for aquifer parameter based on geophysical methods. The Zhagu basin, situated in the Nam Co Lake basin (second largest lake on the TP), is used as a case study. This project is part of the International Research Training Group “Geoecosystems in transition on the Tibetan Plateau” (TransTiP), funded by the DFG.During several field work campaign in July 2018, May 2019 and September 2019 disturbed sediment samples were taken and were analyzed for grain size distribution. Selected sediment layer in the laboratory were tested. Outcome of this analysis is the porosity for each selected sediment layer. Another measurement during field work has been conducted, namely electrical resistivity tomography measurements (ERT). To get better approximation of porosity and sediment characteristics, Archie’s Law is used as model to estimate those properties and later on to compare it to field and laboratory results. Two approaches are implemented (i) calculates the bulk resistivity based on known porosity from the laboratory and known conductivity of pore water measured during field work (ii) calculates the porosity with known conductivity of pore water and the bulk conductivity. For analysis saturated sediment layers were chosen.The investigation shows that both approaches are largely applicable and leading to almost same results and trends of each sediment layer. The best percentage deviation of the modeled bulk resistivity results to the measurement in the field could be achieved by position D11 which is situated near the Nam Co Lake showing a deviation of around 7%. Inside the catchment the percentage deviation is largely increasing. However, the application of Archie’s Law in combination with field and laboratory measurements allows to construct a porosity ranges for future groundwater flow calibration. In addition, the results emphasising the zonation of the subsurface in (un)saturated zones due to the small amount of resistivity.Sediment profiles, ERT measurements, observations, interpretation and conclusion including the comparison of simulated resistivity and simulated porosity to field resistivity and porosity based on laboratory analysis will be shown and discussed in the contribution.