Grassland restoration reduces water yield in the headstream region of Yangtze River

Dynamic Response and Adaptation of Grassland Ecosystems in the Three-River Headwaters Region under Changing Environment: A Review

The Three-River Headwaters Region (TRHR) is crucial to the sustainable development of China and Southeast Asia. The sustainability of grassland ecosystems in the region has been seriously challenged in recent years. This paper reviewed the changes in the grasslands of the TRHR and their responses to climate change and human activities. The review showed that accurate monitoring of grassland ecological information is the basis for effective management. Although alpine grassland coverage and the above-ground biomass of the alpine grassland have generally increased in the region over the past 30 years, the degradation has not been fundamentally curbed. Grassland degradation substantially reduced topsoil nutrients and affected their distribution, deteriorated soil moisture conditions, and aggravated soil erosion. Grassland degradation led to loss of productivity and species diversity, and this is already harming the well-being of pastoralists. The "warm and wet" trend of the climate promoted the restoration of alpine grasslands, but widespread overgrazing is considered as one of the main reasons for grassland degradation, and related differences still exist. Since 2000, the grassland restoration policy has achieved fruitful results, but the formulation of the policy still needs to integrate market logic effectively and strengthen the understanding of the relationship between ecological protection and cultural protection. In addition, appropriate human intervention mechanisms are urgently needed due to the uncertainty of future climate change. For mildly and moderately degraded grassland, traditional methods are applicable. However, the severely degraded "black soil beach" needs to be restored by artificial seeding, and the stability of the plant-soil system needs to be emphasized to establish a relatively stable community to prevent secondary degradation.

Water yield response to plant community conversion caused by vegetation degradation and improvement in an alpine meadow on the northeastern Tibetan Plateau

Water provision is an important ecological function of alpine meadows on the Tibetan Plateau. Quantitative assessment of the effects of vegetation change induced by vegetation degradation and improvement on water yield (WY) in alpine meadows is urgent for rational water and grassland resources conservation and management. Previous studies mainly focused on the effects of vegetation coverage. What is less clear is how the WY of alpine meadow changes under plant community conversion caused by vegetation degradation and improvement. To test the hypotheses that lysimeter drainage (LD) decreases in the vegetation-degraded meadow and recovers in the vegetation-improved meadow, and the LD decreases as the stress tolerance of dominant strategy decreases, in situ lysimeters with intact monoliths of well-vegetated alpine meadows subjected to vegetation intact (sedge-dominated), degraded (forb-dominated) and improved (fast-growing grass-dominated) were employed, and then plant communities among treatments were compared based on the quantitative competitor, stress tolerator, and ruderal (CSR) theory. Compared to the vegetation-intact monoliths, the LD of vegetation-degraded monoliths was 59 % lower owing to the deeper roots and greater aboveground growth. The LD of vegetation-improved monoliths was 83 % higher than that of vegetation-degraded monoliths due to the shallower roots but was 25 % lower than that of vegetation-intact monoliths due to the greater aboveground growth. The LD decreased along a plant community conversion gradient in which the S-selection of the dominance strategy decreased (R² = 0.34, P = 0.022) and the C-selection increased (R² = 0.71, P < 0.001), likely due to the significant covariation between community-weighted CSR strategy with eco-hydrological plant and soil properties. These results indicated that the community conversion caused by vegetation degradation reduces the WY of alpine meadows, and sowing fast-growing grasses can only partly restore this function. Application of stress-tolerant plants for vegetation improvement may be more efficient in recovering the WY of degraded meadows, especially in flat meadows under humid climate.

Root-zone soil moisture estimation based on remote sensing data and deep learning

Soil moisture in the root zone is the most important factor in eco-hydrological processes. Even though soil moisture can be obtained by remote sensing, limited to the top few centimeters (<5 cm). Researchers have attempted to estimate root-zone soil moisture using multiple regression, data assimilation, and data-driven methods. However, correlations between root-zone soil moisture and its related variables, including surface soil moisture, always appear nonlinear, which is difficult to extract and express using typical statistical methods. The artificial intelligence (AI) method, which is advantageous for nonlinear relationship analysis and extraction is applied for root-zone soil moisture estimation, but by only considering its separate temporal or spatial correlations. The convolutional long short-term memory (ConvLSTM) model, known to capture spatiotemporal patterns of large-scale sequential datasets with the advantage of dealing with spatiotemporal sequence-forecasting problem, was used in this study to estimate root-zone soil moisture based on remote sensing-based variables. Owing to limitation of regional soil moisture observation data, the physical model Hydrus-1D was used to generate large and spatiotemporal vertical soil moisture dataset for the ConvLSTM model training and verification. Then, normalized difference vegetation index (NDVI) etc. remote sensing-based factors were selected as predictive variables. Results of the ConvLSTM model showed that the fitting coefficients (R²) of the root-zone soil moisture estimation significantly increased compared to those achieved by Global Land Data Assimilation System products, especially for deep layers. For example, R² increased from 0.02 to 0.60 at depth of 40 cm. This study suggests that a combination of the physical model and AI is a flexible tool capable of predicting spatiotemporally continuous root-zone soil moisture with good accuracy on a large scale.

Multi-scale assessment of water security under climate change in North China in the past two decades

Climate change is projected to affect the hydrological cycles in China, while the effects are expected to vary spatiotemporally. Understanding the variations in water security conditions and their sensitivity to climatic variables is crucial for assessing regional ecosystem responses to climate change. In the present study, we estimated the water yield capacity, an important indicator of water security in North China (NC), at a spatial resolution of 1 km during the last two decades based on the Budyko framework and quantified the sensitivity of water yield change to climate change among different vegetation types. The results showed that the performances of the Budyko framework were reliable both at the pixel scale and across large watersheds. The annual water yield in North China was estimated to be 7.61 ± 2.67 ∗ 10¹⁰ m³/yr, with an average mean water yield (MWY) of 49.51 ± 17.49 mm/yr. The spatial pattern of mean water yield change (MWYC) exhibited high heterogeneity; 46% of the study region was dominated by an increasing trend, while 9.84% was statistically significant (P < 0.05). Compared with temperature, the water yield capacity was more sensitive to precipitation variation. A consistent trend of variation was found in cropland between water yield and precipitation, while negative sensitivity coefficients were found in natural vegetation types. The variation in sensitivity coefficients (Swyp) in natural vegetation showed that in regions with a decrease in precipitation, the variation in water yield capacity also decreased, while in regions with an increase in precipitation from 0 to 8 mm/yr, the water yield capacity first decreased and then increased with precipitation. Our findings suggest that grass and shrubs would be more beneficial to regional water security in North China's revegetation, while afforestation would provide protection for the regional environment from extreme rainfall events.

Attribution of Changes in Streamflow to Climate Change and Land Cover Change in Yangtze River Source Region, China

The quantitative attribution of changes in streamflow to climate change (CC) and land cover change (LCC) for the Yangtze River Source Region (YRSR), China, was assessed. We used a combination of the SWAT model along with the statistical technique one factor at a time (OFAT) and innovative trend analysis (ITA) to achieve the study objectives. The climate and hydrology data from 1961 to 2016 and land-cover maps of 5 years’ difference from 1985 to 2015 were used. The model was calibrated (1964–1989) using a land-cover map of 1985 and validated for 1990–2016. This validated model was further validated for all other land-cover maps used in this study. The SWAT model simulation showed that streamflow had been significantly influenced by CC compared to LCC using land-cover maps of 1985–1990, 1990–1995. However, the SWAT model simulations did not result in further changes in streamflow for land cover maps of 2000–2005, 2005–2010, and 2010–2015 because there have not been any significant changes in land cover after 2000 while the main contributing factor was climate change. The SWAT model simulations showed that the main driver of changes in streamflow in the Yangtze River Source Region is climate change. This study shows that the individual impacts are more critical than combined impacts for designing hydraulic structures, water resources planning and management, and decision-making policies at the regional/basin scale.

Response of hydrological systems to the intensity of ecological engineering

The rapid global construction of ecological engineering has had an important impact on hydrological processes, especially in China. However, previous studies have largely regarded the hydrological system as a "black box" and have formed conclusions by comparing changes before and after ecological engineering; additionally, managers have assumed that the intensity of ecological engineering (IEE) is proportional to the hydrological system effect. The influence processes and mechanisms of the IEE on hydrological systems are unclear. Here, the source region of the Yangtze River (SRYR) in China was adopted as the empirical research area. Based on various data, such as DEM, soil, land use and climate data from 1980 to 1987 and 2004-2015, a Soil and Water Assessment Tool (SWAT) model was constructed, and the response of the hydrological system to the IEE was quantitatively explored. The results showed that the IEE generally displayed an increasing trend, increasing from 10.209 in 2005 to 10.649 in 2015. There was no linear relationship between the IEE and hydrological effects, and the hydrological effects did not increase with increasing IEE but did exhibit obvious stages. Specifically, the four phases - the lag phase, transition phase, sensitive phase, and adaptive phase - had different hydrological response characteristics, sensitivities, structures, and functions. Based on the feedback of the hydrological system, ecological engineering managers should abandon the incorrect assumption of a linear relationship between the two and realize that there is usually a lag phase in the early implementation of ecological engineering that requires a continuous increase in the IEE. Additionally, managers should choose the appropriate IEE, evaluation nodes and periods and prioritize the most sensitive hydrological variables in different stages based on the evaluation purpose and hydrological response, thereby improving the efficiency of ecological engineering and realizing the original goal of ecological protection and restoration.

Mapping Land Use/Cover Dynamics of the Yellow River Basin from 1986 to 2018 Supported by Google Earth Engine

Changes in the land use/cover alter the Earth system processes and affect the provision of ecosystem services, posing a challenge to achieve sustainable development. In the past few decades, the Yellow River (YR) basin faced enormous social and environmental sustainability challenges associated with environmental degradation, soil erosion, vegetation restoration, and economic development, which makes it important to understand the long-term land use/cover dynamics of this region. Here, using three decades of Landsat imagery (17,080 images) and incorporating physiography data, we developed an effective annual land use/cover mapping framework and provided a set of 90 m resolution continuous annual land use/cover maps of the YR basin from 1986 to 2018 based on the Google Earth Engine and the Classification and Regression Trees algorithm. The independent random sampling validations based on the field surveys (640 points) and Google Earth (3456 points) indicated that the overall accuracy of these maps is 78.3% and 80.0%, respectively. The analysis of the land system of the YR basin showed that this region presents complex temporal and spatial changes, and the main change patterns include no change or little change, cropland loss and urban expansion, grassland restoration, increase in orchard and terrace, and increase in forest during the entire study period. The major land use/cover change has occurred in the transitions from forests, grasslands, and croplands to the class of orchard and terrace (19.8% of all change area), which not only increase the greenness but also raised the income, suggesting that YR progress towards sustainable development goals for livelihood security, economic growth, and ecological protection. Based on these data and analysis, we can further understand the role of the land system in the mutual feedback between society and the environment, and provide support for ecological conservation, high-quality development, and the formulation of sustainable management policies in this basin, highlighting the importance of continuous land use/cover information for understanding the interactions between the human and natural systems.

Regional response of grassland productivity to changing environment conditions influenced by limiting factors

Regional differences and regulatory mechanisms of vegetation productivity response to changing environmental conditions constitute a core issue in macroecological researches. To verify the main limiting factors of different macrosystems [temperature-limited Tibetan Plateau (TP), precipitation-limited Mongolian Plateau (MP), and nutrient-limited Loess Plateau (LP)], we conducted a comparative survey of the east-west grassland transects on the three plateaus and explored the factors limiting regional productivity and their underlying mechanisms. The results showed that aboveground net primary productivity (ANPP) of LP (109.10 ± 16.76 g m-2 yr-1) was significantly higher than that of MP (66.71 ± 11.11 g m-2 yr-1) and TP (57.02 ± 10.59 g m-2 yr-1). The response rate of ANPP with environmental changes was different among different plateaus, being closely related to the main limiting factors. On MP, this was precipitation, on LP it was temperature and nutrients, and on TP, it was non-specific, reflecting restriction by the extremely low temperature. After autocorrelation screening of environmental factors, different regions exhibited different productivity response mechanisms. MP was mainly influenced by temperature and precipitation, LP was influenced by temperature and nutrient, and TP was influenced by nutrient, reflecting the modifying effect of the main limiting factors. The effect of each regional environment on ANPP was 72.56% on average and only 27.18% after simple regional integration. The regional model could optimize the simulation error of the integrated model, and the relative deviations in MP, LP, and TP were reduced by 31.76%, 17.22%, and 2.23%, respectively. These findings indicate that the grasslands on the three plateaus may have different or even the opposite mechanisms to control productivity.

Natural and anthropogenic influences on the recent droughts in Yellow River Basin, China

Drought in human-dominated environments cannot be seen as a unidirectional hazard as its characteristics are derived and modified by both natural climate variability and human influences. In this study, we applied an observation-modeling framework to quantify the natural and human controls on drought characteristics based on simulated and observed hydrometeorological data from six sub-catchments of the Yellow River Basin in China. A calibrated Soil and Water Assessment Tool (SWAT) was applied to simulate the naturalized situation, whereas Standardized Precipitation Index, Streamflow Drought Index, and Soil Moisture Deficit Index were used to characterize drought at meteorological, agricultural and hydrological aspects. Furthermore, various statistical tools, i.e., bivariate correlation analysis, heat maps, and linear models based on multiple regression, were applied to find the statistical relationships between drought characteristics and the multiple influencing factors. The results revealed that the duration of precipitation's dry spells was important for agricultural drought duration, whereas hydrological drought severity and duration highly depended on soil moisture. Meteorological to agricultural drought propagation mechanism was primarily affected by land use/land cover change (LULCC), whereas meteorological to hydrological propagation was influenced mostly by direct human activities (DHA). The human modifiers were found to have both positive and negative effects on drought severity and duration. For instance, agricultural practices and afforestation intensified soil moisture drought, while grassland restoration had a positive impact on agricultural drought severity. Deforestation enhanced hydrological drought, while afforestation and grassland restoration had the opposite effect. Hydrological drought severity and duration were largely amplified by DHA but enhanced by irrigation return flow. Spatially, sub-catchments with high urbanization and irrigated cropland were found to have shorter and less severe droughts than those dominated by grassland.

Distinguishing the Relative Contribution of Environmental Factors to Runoff Change in the Headwaters of the Yangtze River

The change in river flows at the basin scale reflects the combined influences of changes in various environmental factors associated with climatic and underlying surface properties. Distinguishing the relative contribution of each of these factors to runoff change is critical for sustainable water resource management, but it is also challenging. The headstream region of the Yangtze River, known as “China’s Water Tower”, has undergone a significant runoff change over the past decades. However, the relative contribution of environmental factors to runoff change is still unclear. Here, we designed a series of detrending experiments based on a grid-based hydrological model to quantify the combined influences of multiple environmental factors on runoff change and the relative contribution of an individual factor to runoff change. The results indicate that changes in climate and vegetation significantly increased water yield in the study basin over the past three decades, and the increase in water yield primarily came from the contribution from the upstream of the basin. On the basin scale, the change in precipitation dominated the runoff change that contributed up to 113.2% of the runoff change, followed by the wind speed change with a contribution rate of −15.1%. Other factors, including changes in temperature, relative humidity, sunshine duration (as a surrogate for net radiation), and albedo (as a surrogate for vegetation) had limited effects on runoff change, and the contribution rate of these factors to runoff change ranged from −5% to 5%. On spatial patterns, the influences of changes in some environmental factors on runoff changes were affected by elevation, particularly for temperature. The rising temperature had mixed effects on runoff change, which generally increased water yield at high altitudes of the basin but decreased water yield at low altitudes of the basin.

A Landsat-based vegetation trend product of the Tibetan Plateau for the time-period 1990-2018

The Tibetan Plateau is a unique, biodiverse ecosystem with an important role in the climate and hydrological system of Asia. Its vegetation supports important functions including fodder provision, erosion prevention and water retention. Assessing vegetation trends of the Tibetan Plateau is crucial to understand effects of recent climate and land-use changes. Most existing vegetation trend products covering the entire Tibetan Plateau have a coarse spatial grain and cover short temporal ranges. This hampers their applicability in studies conducted at local scales where land-use decisions take place and at time scales where climate changes become apparent. Here, we present vegetation trend products for the entire Tibetan Plateau at a spatial resolution of 30 m for the time period 1990-2018. These products include results of a modified Mann-Kendall trend test applied to annual Landsat-based NDVI mosaics, composed from all satellite observations acquired during the vegetation periods as well as NDVI difference images. These data can be valuable to many researchers including for example wildlife ecologists, rangeland experts and climate change researchers.

Partitioning climate and human contributions to changes in mean annual streamflow based on the Budyko complementary relationship in the Loess Plateau, China

Reliable attribution of changes in streamflow is fundamental to our understanding of the hydrological cycle and is needed to enable decision makers to manage water resources in a sustainable way. Here, we used a new attribution method based on the Budyko framework (complementary method) to quantify the contributions of climate change and human activities to the changes in annual streamflow in 22 catchments on China's Loess Plateau during the past three decades. Our results showed that after the Grain-for-Green (GFG) project, the annual streamflow decreased by 36% on average (3-72%), with reductions being more intense in northern catchments. The sensitivity of streamflow to precipitation and potential evapotranspiration also decreased, with a mean rate of -0.7 mm yr^-1/mm yr^-1 and -0.2 mm yr^-1/mm yr^-1, respectively. Using the upper and lower bounds of the human effects on streamflow from the complementary method as a reference, we found that these effects at half of the stations were under- or over-estimated by the total differential method. The contribution analysis from the complementary method showed that although human activities decreased streamflow by 26% (or 54% as a relative value) on average, the contribution of potential evapotranspiration alone to the decrease in streamflow was 9% (42%), highlighting the important role of increasing atmospheric moisture demand in the water cycle. In addition, the 5-year incremental analysis showed that the impacts of climate and human activities on streamflow had strong spatiotemporal variability.

Clipping has stronger effects on plant production than does warming in three alpine meadow sites on the Northern Tibetan Plateau

The relative effects of warming and clipping on vegetation growth are not fully understood. Therefore, we compared the relative effects of experimental warming and clipping on the normalised difference vegetation index (NDVI), green NDVI (GNDVI), soil-adjusted vegetation index (SAVI), aboveground biomass (AGB) and gross primary production (GPP) in three alpine meadow sites (A, B and C) on the Northern Tibetan Plateau from 2013 to 2015. There were no obvious effects of experimental warming on the NDVI, GNDVI, SAVI, AGB and GPP at the three sites, which were most likely attributed to experimental warming-induced warming and drying conditions. In contrast, clipping significantly decreased the NDVI, SAVI and AGB by 27.8%, 31.3% and 18.2% at site A, by 27.1%, 31.8% and 27.7% at site B, and by 12.3%, 15.1% and 17.6% at site C, respectively. Clipping also significantly reduced the GNDVI and GPP by 11.1% and 28.2% at site A and by 18.9% and 33.7% at site B, respectively. Clipping marginally decreased the GNDVI by 8.7% (p = 0.060) and GPP (p = 0.082) by 14.4% at site C. Therefore, clipping had stronger effects on vegetation growth than did warming in the three alpine meadow sites on the Tibetan Plateau.