ABSTRACT:The relationship between forests and streamflows has long been an important research interest in China. The purpose of this paper is to summarize progress and lessons learned from the forest-streamflow studies over the past four decades in China. To better measure the research gaps between China and other parts of the world, a brief global review on the findings from paired watershed studies over the past 100 years was also provided. In China, forest management shifted in the later 1990s from timber harvesting to forest restoration. Forest-streamflow research was accordingly changed from assessing harvesting impacts to evaluating both harvesting and forestation effects. Over the past four decades, Chinese forest hydrology research has grown substantially. Significant progress has been made on measuring individual processes, but little solid, long-term data were available to assess the relationship between forest changes and streamflows because of an absence of standard paired watersheds. In addition, misuse of statistical analyses was often found in the literature. A unique opportunity exists in China to study the forestation effects on streamflow as several large-scale forestation programs are being implemented. Such an opportunity should include a robust paired watershed design under an integrated watershed ecosystem framework to avoid repeating the lessons already learned. Recommendations on future forest-streamflow research directions in China are provided.
Natural forests in southern China have been severely logged due to high human demand for timber, food, and fuels during the past century, but are recovering in the past decade. The objective of this study was to investigate how vegetation cover changes in composition and structure affected the water budgets of a 9.6-km 2 Dakeng watershed located in a humid subtropical mountainous region in southern China. We analyzed 27 years (i.e., 1967-1993) of streamflow and climate data and associated vegetation cover change in the watershed. Land use ⁄ land cover census and Normalized Difference of Vegetation Index (NDVI) data derived from remote sensing were used to construct historic land cover change patterns. We found that over the period of record, annual streamflow (Q) and runoff ⁄ precipitation ratio did not change significantly, nor did the climatic variables, including air temperature, Hamon's potential evapotranspiration (ET), pan evaporation, sunshine hours, and radiation. However, annual ET estimated as the differences between P and Q showed a statistically significant increasing trend. Overall, the NDVI of the watershed had a significant increasing trend in the peak spring growing season. This study concluded that watershed ecosystem ET increased as the vegetation cover shifted from low stock forests to shrub and grasslands that had higher ET rates. A conceptual model was developed for the study watershed to describe the vegetation cover-streamflow relationships during a 50-year time frame. This paper highlighted the importance of eco-physiologically based studies in understanding transitory, nonstationary effects of deforestation or forestation on watershed water balances.
Rainfall runoff erosivity (R) is one key climate factor that controls water erosion. Quantifying the effects of climate change-induced erosivity change is important for identifying critical regions prone to soil erosion under a changing environment. In this study we first evaluate the changes of R from 1970 to 2090 across the United States under nine climate conditions predicted by three general circulation models for three emissions scenarios (A2, A1B, and B1) from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Then, we identify watersheds that are most vulnerable to future climate change in terms of soil erosion potential. We develop a novel approach to evaluate future trends of R magnitude and variance by incorporating both the rate of change with time as well as the level of agreement between climatic projections. Our results show that mean decadal R values would increase with time according to all nine climatic projections considered between 1970 and 2090. However, these trends vary widely spatially. In general, catchments in the northeastern and northwestern United States are characterized by strong increasing trends in R, while the trends in the midwestern and southwestern United States are either weak or inconsistent among the nine climatic projections considered. The northeastern and northwestern United States will likely experience a significant increase in annual variability of R (i.e., increase in extreme events). Conversely the variability of R is unlikely to change in large areas of the Midwest. At the watershed scale (8-digit Hydrologic Unit Code), the mean vulnerability to erosion scores vary between -0.12 and 0.35 with a mean of 0.04. The five hydrologic regions with the highest mean vulnerability to erosion are 5, 6, 2, 1, and 17, with values varying between 0.06 and 0.09. These regions occupy large areas of Ohio, Maryland, Indiana, Vermont, and Illinois, with mean erosion vulnerability score statewide above 0.08. Future watershed management aiming at reducing soil erosion should focus on areas with the highest soil erosion vulnerability identified by this study.
The general relationships between vegetation and water yield under different climatic regimes are well established at a small watershed scale in the past century. However, applying the basic theories to evaluate the regional effects of land cover change on water resources has been rarely done due to the complex interactions of vegetation and climatic variability and hydrologic processes at the large scale. The objective of this study was to explore ways to examine the spatial and temporal effects of a large ecological restoration project on water yield across the Loess Plateau region in Northern China. We estimated annual water yield as the difference between precipitation input and modeled actual evapotranspiration (ET) output. We constructed a monthly ET model using published eddy flux ET measurements, ET estimates derived from local watershed streamflow data. We validated the ET models at a watershed and regional levels. The model was then applied to examine regional water yield under land cover change and climatic variability during the implementation of the Grain-for-Green (GFG) project during 1999–2007. We found that water yield in 38% of the Loess Plateau area as a whole might have decreased (1–48 mm yr<sup>−1</sup>) as a result of land cover change alone. However, combined with climatic variability, 37% of the study area might have seen a decrease in water yield with a range of 1–54 mm yr<sup>−1</sup>, and 35% of the study area might have seen an increase with a range of 1–10 mm yr<sup>−1</sup>. Across the study region, climate variability masked or strengthened the water yield response to vegetation restoration. The absolute annual water yield change due to vegetation restoration varied with precipitation regimes with the highest in wet years, but the relative water yield changes were most pronounced in dry years. When compared to findings at the plot or catchment-scale, this study suggested that regional hydrologic effects of vegetation restoration practices had a rather complex pattern due to both spatial differences in climatic regimes and vegetation response. We concluded that the effects of land cover change associated with ecological restoration varied greatly over time and space and were strongly influenced by climatic variability in the arid region. The current regional vegetation restoration projects have variable effects on local water resources across the region. Land management planning must consider the influences of spatial climate variability and long-term climate change on water yield to be more effective and achieve environmental sustainability
Quantifying the hydrologic responses to land use/land cover change and climate variability is essential for integrated sustainable watershed management in water limited regions such as the Loess Plateau in Northwestern China where an adaptive watershed management approach is being implemented. Traditional empirical modeling approach to quantifying the accumulated hydrologic effects of watershed management is limited due to its complex nature of soil and water conservation practices (e.g., biological, structural, and agricultural measures) in the region. Therefore, the objective of this study was to evaluate the ability of the distributed hydrologic model, MIKE SHE to simulate basin runoff. Streamflow data measured from an overland flow‐dominant watershed (12 km2) in northwestern China were used for model evaluation. Model calibration and validation suggested that the model could capture the dominant runoff process of the small watershed. We found that the physically based model required calibration at appropriate scales and estimated model parameters were influenced by both temporal and spatial scales of input data. We concluded that the model was useful for understanding the rainfall‐runoff mechanisms. However, more measured data with higher temporal resolution are needed to further test the model for regional applications.
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