Abstract Baseflow plays a vital role in protecting the environment and ensuring a stable water supply for farming. There are still gaps in the current understanding of baseflow convergence rates in the humid region due to the abundance of rainfall and the high‐water table. Therefore, this study focused on the evolution and hysteresis characteristics of baseflow in humid basins of southeastern China. The baseflow ensemble simulation (BES) method was established to improve the reliability and applicability of baseflow simulation. We suggest a way of differentiating the wet and dry seasons based on the multi‐year average monthly baseflow index (BFI) to determine the intra‐annual distribution of water effectively and simply. The hydrological hysteresis effect of baseflow on precipitation is revealed by characterizing baseflow response to precipitation under precipitation events during wet and dry seasons. A methodology for assessing the performance of baseflow simulation was proposed from observations of streamflow and precipitation. We found that the BES method performed better in baseflow simulation than other single separation methods. Using the BES method, the lag time of baseflow to precipitation during the wet and dry seasons was found to be 3.09 and 4.04 days after utilizing the BFI to divide the hydrological situation into wet and dry seasons. Additionally, precipitation had nearly twice as much intensity influence on baseflow during the dry season compared to the wet season. These findings have significant ramifications for the use, management, and planning of water resources in humid areas of China.
Understanding the impact of climate change and human activities on the hydrological cycle of any watershed can provide a scientific basis for regional water resource planning, flood management, and disaster mitigation. An improved three-parameter hydrological model (CM) based on monthly water balance using an exponential equation to depict the distribution of groundwater storage capacity was developed and evaluated. The model uses Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) rainfall data as input, with the Zhejiang Province as the case application, and the effects of climate change and human activities on streamflow changes were assessed by separating environmental variables in this study. The results indicate that APHRODITE data has excellent monthly accuracy, with a mean correlation coefficient (CC) of more than 0.96 and an average absolute percentage bias (Pbais) of less than 5%. The three models are relatively close in their ability to simulate high flows, but the CM simulated low flow is better than the other two models. Positive and negative Pbais phenomena occur in the CM model in each catchment, and absolute levels are regulated by 5%. Furthermore, the CM model’s average Nash efficiency coefficient (NSE) is greater than 0.9, indicating that it can correctly fulfill the water balance. The results are more consistent throughout multiple catchments in each watershed using Budyko-based and hydrological model technique to evaluate the influence of climate change and human activities on streamflow. Climate change dominated streamflow variations in 18 of the 21 catchments in Zhejiang Province, whereas human activities dominated the rest. The findings of the study will be used to influence the management, development, and usage of water resources in the watershed.
The vegetation restoration project, named the Grain to Green Program, has been operating for more than ten years in the upper reaches of the Beiluo River basin, located in the Loess Plateau of China. It is significant to be able to estimate the success of preventing soil erosion. In this study, the Revised Universal Soil Loss Equation (RUSLE) and the Sediment Distributed Delivery (SEDD) model were used to assess the annual soil loss derived from water erosion. The results showed that the study area suffered from primary land use changes, with increasing grassland and forest and decreasing farmland from 1990 to 2010. Based on that, the average soil erosion modulus decreased from 18,189.72 t/(km2 a) in 1990–7408.93 t/(km2 a) in 2000 and 2857.76 t/(km2 a) in 2010. Compared with 1990, the average soil erosion modulus decreased by 59.0% and 84.3% for 2000 and 2010, respectively. Benefiting from the increased vegetation coverage and improved ecological environment, the soil erosion in this study area clearly declined. This research also found that the distribution of the three years of soil erosion was similarly based on topographic factors. The soil erosion modulus varied with different land use types and decreased in the order of residential area>farmland>grassland>forest. The average soil erosion modulus gradually increased with the increase of the slope gradient, and 76.08% of the total soil erosion was concentrated in the region with a gradient more than 15 degrees. The soil erosion modulus also varied with slope aspects in the order of sunny slope>half-sunny slope>half-shady slope>shady slope. This research provides useful reference for soil and water conservation and utilization in this area and offers a technical basis for using the RUSLE to estimate soil erosion in the Loess Plateau of China.
In this paper, we consider a new method for forest canopy height estimation using TanDEM-X single-pass radar interferometry. We exploit available information from sample-based, space-borne LiDAR systems, such as the Global Ecosystem Dynamics Investigation (GEDI) sensor, which offers high-resolution vertical profiling of forest canopies. To respond to this, we have developed a new extended Fourier-Legendre series approach for fusing high-resolution (but sparsely spatially sampled) GEDI LiDAR waveforms with TanDEM-X radar interferometric data to improve wide-area and wall-to-wall estimation of forest canopy height. Our key methodological development is a fusion of the standard uniform assumption for the vertical structure function (the SINC function) with LiDAR vertical profiles using a Fourier-Legendre approach, which produces a convergent series of approximations of the LiDAR profiles matched to the interferometric baseline. Our results showed that in our test site, the Petawawa Research Forest, the SINC function is more accurate in areas with shorter canopy heights (<~27 m). In taller forests, the SINC approach underestimates forest canopy height, whereas the Legendre approach avails upon simulated GEDI forest structural vertical profiles to overcome SINC underestimation issues. Overall, the SINC + Legendre approach improved canopy height estimates (RMSE = 1.29 m) compared to the SINC approach (RMSE = 4.1 m).
Baseflow estimation and evaluation are two critical and essential tasks for water quality and quantity, drought management, water supply, and groundwater protection. Observed baseflows are rarely available and are limited to focused pilot studies. In this study, an exhaustive evaluation of four different baseflow separation methods (HYSEP, WHAT, BFLOW, and PART) using surrogates of observed baseflows estimated with the conductivity mass balance (CMB) method is carried out using data from several streamflow gauging sites from the South Atlantic-Gulf (SAG) region comprised of nine states in the Southeastern U.S. Daily discharge data from 75 streamflow gauging sites for the period 1970–2013, located in the least anthropogenically affected basins in the SAG region were used to estimate the baseflow index (BFI), which quantifies the contribution of baseflow from streamflows. The focus of this study is to compare the four different baseflow separation methods and calibrate and validate these methods using CMB method based estimates of baseflows to evaluate the variation of BFI values derived from these methods. Results from the study suggest that the PART and HYSEP methods provide the highest and lowest average BFI values of 0.62 and 0.52, respectively. Similarities in BFI values estimated from these methods are noted based on a strong correlation between WHAT and BFLOW. The highest BFI values were found in April in the eastern, western, and central parts of the SAG region, and the highest contribution of baseflow to the streamflow was noted in October in the southern region. However, the lowest BFI values were noted in the month of September in all regions of SAG. The calibrated WHAT method using data from the CMB method provides the highest correlation as noted by the coefficient of determination. This study documents an exhaustive and comprehensive evaluation of baseflow separation methods in the SAG region, and results from this work can aid in the selection of the best method based on different metrics reported in this study. The use of the best method can aid in the short and long term management of low flows at a regional level that supports a sustainable aquatic environment and mitigates the effects of droughts effectively.
The erosion characteristics of the upper slope runoff and the slope gully erosion relationship are discussed based on the data of runoff and sediment yield from gauging stations in the loess areas at the middle reaches of the Yellow River. Sources of sediments in typical small catchment are determined based on the concept of net increment of sediment yield by using analytical method of sediment formation at different positions in a catchment. The result shows that sediments in a small catchment at the middle reaches of the Yellow River mainly come from slopes. This paper indicated that the sediment sources from slopes are roughly 55, and 85 percent of the total sediment yield of the small catchments in Yangdaogou, and Nanxiaohegou, respectively, due to impacts of varying degrees from upper slope runoff. Under a critical condition, erosion characteristics of slope would change. In yangdaogou and wangmaogou , the critical value are about 319 kg/m 3 and 362 kg/m 3 under multi years (or multi times) rainfall condition, respectively.
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