Periodic variations of rainfall, groundwater level and dissolved radon from the perspective of wavelet analysis: a case study in Tengchong, southwest China

Tao, Yang; Wang, Guangcai

doi:10.1007/s12665-021-09785-2

Cited by 7 publications

(3 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The optimal GWSA lag time relative to the input predictors was found by changing the lag time from 0 months to 5 months to obtain the maximum correlation between the GWSAs and the input variables. Precipitation, one of the main sources of groundwater recharge in arid regions [58], was found to be the most relevant to GWSAs with a lag time of 3 months (see Table 2) [57,59,60]. SMC (soil moisture in soil depths ≥ 40 cm) was strongly correlated with GWSAs, exhibiting the smallest lag time (0 to 1 month), indicating that GWS responds more immediately to deep SMC than to other input predictors.…”

Section: Influence Of Time-lag Effectmentioning

confidence: 99%

Constructing GRACE-Based 1 km Resolution Groundwater Storage Anomalies in Arid Regions Using an Improved Machine Learning Downscaling Method: A Case Study in Alxa League, China

Wang

2023

Remote Sensing

View full text Add to dashboard Cite

Using the Gravity Recovery and Climate Experiment (GRACE) satellite to monitor groundwater storage (GWS) anomalies (GWSAs) at the local scale is difficult due to the low spatial resolution of GRACE. Many attempts have been made to downscale GRACE-based GWSAs to a finer resolution using statistical downscaling approaches. However, the time-lag effect of GWSAs relative to environmental variables and optimal model parameters is always ignored, making it challenging to achieve good spatial downscaling, especially for arid regions with longer groundwater infiltration paths. In this paper, we present a novel spatial downscaling method for constructing GRACE-based 1 km-resolution GWSAs by using the back propagation neural network (BPNN) and considering the time-lag effect and the number of hidden neurons in the model. The method was validated in Alxa League, China. The results show that a good simulation performance was achieved by adopting varying lag times (from 0 to 4 months) for the environmental variables and 14 hidden neurons for all the networks, with a mean correlation coefficient (CC) of 0.81 and a mean root-mean-square error (RMSE) of 0.70 cm for each month from April 2002 to December 2020. The downscaled GWSAs were highly consistent with the original data in terms of long-term temporal variations (the decline rate of the GWSAs was about −0.40 ± 0.01 cm/year) and spatial distribution. This study provides a feasible approach for downscaling GRACE data to 1 km resolution in arid regions, thereby assisting with the sustainable management and conservation of groundwater resources at different scales.

show abstract

Section: Influence Of Time-lag Effectmentioning

confidence: 99%

Constructing GRACE-Based 1 km Resolution Groundwater Storage Anomalies in Arid Regions Using an Improved Machine Learning Downscaling Method: A Case Study in Alxa League, China

Wang

2023

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Therefore, to gain a more comprehensive understanding of the implications of water conservation project implementation on the DTG dynamics, it is crucial to employ sophisticated statistical techniques to meticulously delineate its dynamic patterns. Currently, sophisticated statistical approaches employed in the analysis of DTG dynamics include wavelet transform (WT), empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), and complementary ensemble empirical mode decomposition (CEEMD) [19][20][21][22][23][24][25][26][27][28]. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) proposed by Torres et al [29], which adds specific white noise to each scale residual component of the decomposition and obtains the intrinsic mode function (IMF) by calculating the unique residual, can efficiently separate the periodic factors influencing signal trends from the inherent trend of the signal.…”

Section: Introductionmentioning

confidence: 99%

Evolution Trend of Depth to Groundwater and Agricultural Water-Saving Measure Threshold under Its Constraints: A Case Study in Helan Irrigated Areas, Northwest China

Chang,

Yang,

et al. 2024

Water

View full text Add to dashboard Cite

Water conservation is imperative for alleviating water shortages and fostering the establishment of a water-saving society. However, the implementation of water-saving measures caused an increase in the depth to groundwater, resulting in ecological issues. Therefore, reasonable water saving should consider the appropriate depth to groundwater and its evolution trend. This study focuses on the Helan irrigation area in Ningxia as the research subject, aiming to establish thresholds for agricultural water-saving measures while considering constraints by depth to groundwater. The evolution trend of depth to groundwater from 1995 to 2018 was analyzed using the k-Shape cluster and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) methods. Then, the thresholds of agricultural water-saving measures involved comparing groundwater numerical simulation results for water-saving scenarios, with the control area of ecological groundwater table depth and water shortage rate serving as the evaluation indices. The thresholds for implementing agricultural water-saving measures are as follows: the canal water utilization coefficient is set at 0.62; the proportion of water-efficient irrigation areas to effective irrigation areas should be 40% in the Yellow River irrigation area and 90% in the pumps-up Yellow River irrigation area; additionally, a reduction of 75% in the rice planting area is targeted.

show abstract

“…Various hydrology and water resource-related disciplines have recently shown an increased interest in using wavelet analysis. Particularly in terms of periodicity, numerous research studies have demonstrated that wavelet analysis is a useful tool for characterizing and analyzing climatic and hydrological data [22][23][24][25][26][27][28][29][30][31], and, also, the frequency domain variable structures of various climatic or hydrological variables can be examined and synthesized using wavelet analysis, which is also an effective method for exploring relationships between them [32][33][34][35][36][37][38][39][40][41]. Recent research has shown that wavelet analysis is an effective technique for identifying irregularly distributed multiscale characteristics in hydrometeorological data, and, also, the ability to establish quantitative correlations between various observation series using wavelet-based expressions has been demonstrated [42][43][44][45][46][47][48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

Wavelet Analysis and the Information Cost Function Index for Selection of Calibration Events for Flood Simulation

Jam-Jalloh,

Liu,

Wang

et al. 2023

Water

View full text Add to dashboard Cite

Globally, floods are a prevalent type of natural disaster. Simulating floods is a critical component in the successful implementation of flood management and mitigation strategies within a river basin or catchment area. Selecting appropriate calibration data to establish a reliable hydrological model is of great importance for flood simulation. Usually, hydrologists select the number of flood events used for calibration depending on the catchment size. Currently, there is no numerical index to help hydrologists quantitatively select flood events for calibrating the hydrological models. The question is, what is the necessary and sufficient amount (e.g., 10 events) of calibration flood events that must be selected? This study analyses the spectral characteristics of flood data in Sequences before model calibration. The absolute best set of calibration data is selected using an entropy-like function called the information cost function (ICF), which is calculated from the discrete wavelet transform (DWT) decomposition results. Given that the validation flood events have already been identified, we presume that the greater the similarity between the calibration dataset and the validation dataset, the higher the performance of the hydrological model should be after calibration. The calibration datasets for the Tunxi catchment in southeast China were derived from 21 hourly flood events, and the calibration datasets were generated by arranging 14 flood events in sequences from 3 to 14 (i.e., a Sequence of 3 with 12 sets (set 1 = flood events 1, 2, 3; set 2 = flood events 2, 3, 4, …, and so on)), resulting in a total of 12 sequences and 78 sets. With a predetermined validation set of 7 flood events and the hydrological model chosen as the Hydrologic Engineering Center (HEC–HMS) model, the absolute best calibration flood set was selected. The best set from the Sequence of 10 (set 4 = S10′) was found to be the absolute best calibration set of flood events. The potential of the percentile energy entropy was also analyzed for the best calibration sets, but the ICF was the most consistent index to reveal the ranking based on similarity with model performance. The proposed ICF index in this study is helpful for hydrologists to use data efficiently with more hydrological data obtained in the new era of big data. This study also demonstrates the possibility of improving the effectiveness of utilizing calibration data, particularly in catchments with limited data.

show abstract

Periodic variations of rainfall, groundwater level and dissolved radon from the perspective of wavelet analysis: a case study in Tengchong, southwest China

Cited by 7 publications

References 53 publications

Constructing GRACE-Based 1 km Resolution Groundwater Storage Anomalies in Arid Regions Using an Improved Machine Learning Downscaling Method: A Case Study in Alxa League, China

Constructing GRACE-Based 1 km Resolution Groundwater Storage Anomalies in Arid Regions Using an Improved Machine Learning Downscaling Method: A Case Study in Alxa League, China

Evolution Trend of Depth to Groundwater and Agricultural Water-Saving Measure Threshold under Its Constraints: A Case Study in Helan Irrigated Areas, Northwest China

Wavelet Analysis and the Information Cost Function Index for Selection of Calibration Events for Flood Simulation

Contact Info

Product

Resources

About