Precise evaluation of the correlations among precipitation, groundwater and river water enhance our understanding on regional hydrological circulation and water resource management. The innovative and efficient use of wavelet analysis has been able to identify significant interactions in the spatial and temporal domains and to estimate the recharge travel time. In this paper, a wavelet analysis was utilized to analyse 43 years of monthly, and 2 years of daily, precipitation, river level and groundwater level data in the Yoshino River Basin, Japan. There were two main results: (1) There was a significant influence of precipitation and river on groundwater, with a periodicity of 4–128 days, 1 year and 2–7 years. The periodicity of 1 year was correlated with seasonal variability. The significant interaction at 4–128 days mainly occurred in the rainy season. The 2–7-year oscillation of aquifer water levels was determined by precipitation. (2) The recharge-water travel times in the study area estimated from the arrow patterns in the precipitation–groundwater wavelet coherence (WTC) were consistent for each observation well. The response times of the aquifer to precipitation were 1 day and 3–6 days in 2013 and 2014, respectively. The different time lags were likely determined by the timing of maximum daily precipitation.
The Danjiang River being the main tributary of the Hanjiang river, is the main water source of the south-to-north water diversion project in China, which is benefit from the protection of ecological environment. As the main reasons for ecological degradation, the land use changing and severe soil erosion attacted considerable attention in recent years. Based on the land use data and measured runoff and sediment data, the landscape pattern index analysis method and statistical analysis method were employed to explore the relationship between landscape pattern indexes and runoff and sediment in Danjiang River Basin (DRB). The results show that the runoff and sediment of the river present a downward trend from 1985 to 2018. The forestland was the dominant type of land use, and the growth rate of grassland was the highest. Results also show that the patch density (PD), the interspersion and juxtaposition (IJI), the edge density (ED), CONTAG, DIVISION and the largest patches index (LPI) have the same trend, indicating that the fragmentation degree of landscape, the connectivity between landscapes, and the richness of landscape increased. In addition, the shannon’s diversity index (SHDI) and IJI were positively associated with the runoff at landscape level, number of patches (NP), PD, ED, and CONTAG were negatively associated with sediment, and CONTAG was positively correlated with sediment. At class level, the NP, PD, LSI, and IJI of forestland, the NP, PD, and DIVISION of cropland, the LPI of grassland, and the NP, PD, and LSI of construction land were negatively correlation with runoff. The LSI and ED of grassland and the LPI of construction land were positively correlation with runoff. And the LSI, IJI, and ED of forestland and the LSI, IJI, and ED were negatively correlation with sediment.
Precipitation has been recognized as the most critical meteorological parameter in hydrological studies. Recent developments in space technology provide cost-effective alternative ground-based observations to simulate the hydrological process. Here, this paper aims to evaluate the performance of satellite-based datasets in the hydrological modeling of a sensitive area in terms of water quality and safety watershed. Three precipitation products, i.e., rain gauge observations (RO), the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS), and Tropical Rainfall Measuring Mission Multi-satellite (TRMM) products, were used to develop the Soil and Water Assessment Tool (SWAT) model to simulate the streamflow in the Danjiang River Basin (DRB). The results show that: (1) these three precipitation products have a similar performance with regard to monthly time scale compared with the daily scale; (2) CMADS and TRMM performed better than RO in the runoff simulations. CMADS is a more accurate dataset when combined with satellite-based and ground-based data; (3) the results indicate that the CMADS dataset provides reliable results on both monthly and daily scales, and CMADS is a possible alternative climate product for developing a SWAT model for the DRB. This study is expected to serve as a reference for choosing the precipitation products for watersheds similar to DRB where the rain gauge data are limited.
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