Modeling of groundwater level fluctuations using dendrochronology in alluvial aquifers

Gholami, Vahid; Chau, Kwok Wing; Fadaee, F.; Torkaman, Javad; Ghaffari, A.

doi:10.1016/j.jhydrol.2015.09.028

Cited by 225 publications

(90 citation statements)

References 68 publications

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“…The accuracy of 3B42V7 and CMORPH at the monthly scale is higher, and the accuracy of 3B42V7 is higher than that of CMORPH. The monthly rainfall data from satellite-based rainfall products can be parameters that are input to the hydrological model and data assimilation [51][52][53][54]. In the future, we will integrate the two evaluation methods and deeply analyze the calculation of different error statistics to elucidate insights into rainfall detection.…”

Section: Discussionmentioning

confidence: 99%

Accuracy Evaluation of Two High-Resolution Satellite-Based Rainfall Products: TRMM 3B42V7 and CMORPH in Shanghai

Jiang

Wen

et al. 2018

Water

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Satellite-based rainfall products have extensive applications in global change studies, but they are known to contain deviations that require comprehensive verification at different scales. In this paper, we evaluated the accuracies of two high-resolution satellite-based rainfall products: the Tropical Rainfall Measurement Mission (TRMM) rainfall product 3B42V7 and the Climate Prediction Center morphing (CMORPH) technique from January 2010 to December 2011 in Shanghai, by using categorical metrics (Probability of Detection, False Alarm Ratio, and Critical Success Index) and statistical indicators (Mean Absolute Error, Root Mean Square Error, Relative Bias, and Correlation Coefficient). Our findings show that, firstly, CMORPH data has a higher accuracy than 3B42V7 at the daily scale, but it underestimates the occurrence frequency of daily rainfall for some intensity ranges. Most errors of the two products are distributed between −10 and 10 mm/day. Second, at the monthly scale, the total accuracy of 3B42V7 is higher than CMORPH in terms of the value of the Correlation Coefficient (CC) and Relative Bias (RB). Finally, CMORPH brings about daily rainfall detection results from categorical metrics computation better than 3B42V7. Generally, the two satellite-based rainfall products show a high correlation with rain gauge data in Shanghai, particularly in spring and winter. Unfortunately, in summer, both of them do not perform well in detecting the short-duration heavy rainfall events. Overall, the relatively poor data accuracy has limited their further applications in Shanghai and similar urban areas.

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Section: Discussionmentioning

confidence: 99%

Accuracy Evaluation of Two High-Resolution Satellite-Based Rainfall Products: TRMM 3B42V7 and CMORPH in Shanghai

Jiang

Wen

et al. 2018

Water

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“…Furthermore, artificial neural network and other new methods were also used in this research for prediction of precipitation. We will compare and combine these methods in further studies [37][38][39][40][41][42]. The influences of this precipitation fluctuation change to vegetation change will also be further studied.…”

Section: Discussionmentioning

confidence: 99%

Annual Precipitation Fluctuation and Spatial Differentiation Characteristics of the Horqin Region

et al. 2017

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Abstract:Precipitation is the main water source for vegetation survival in arid and semi-arid areas. However, previous studies always focus on the effects of precipitation in different time scales, but ignore the effects of precipitation in different spatial scales. To further study the effects of precipitation fluctuation in different spatial scales, we used the wavelet analysis method to analyze its temporal and spatial change based on data from eighteen meteorological stations during 1961-2015 in Horqin region. Results showed that: (1) from the overall tendency of precipitation changes, the precipitation inter-annual variations in Horqin region had the tendency of gradually decreasing from the southeast (District IV) to the northwest; (2) the precipitation anomalies of District I-IV between 1960 and 1980 were small and approximate to the normal value; (3) in the time scale of 23-32 years, the cyclical fluctuations were very significant and the annual precipitation underwent two cyclical fluctuations from a period of low precipitation to a period of high precipitation; and (4) as results of analyzing the spatial wavelet variance of sub-region, the main cycle of precipitation in District I, District II and District III was between 10 and 11 years, while the main cycle of precipitation in District IV was 25 years. The main conclusions include the following. (1) This region tended to be arid, and the precipitation gradually decreased from the southeast (District IV) to northwest (District I). (2) The influence of spatial differentiation characteristics on precipitation fluctuation in this region was cyclical fluctuation, which gradually decreased from the southeast to the northwest. The length of the cyclical change period gradually shortened. In the first main cycle, whose annual precipitation changes were most significant, the changing characteristic was District IV and District I decreased from 25 years to 10 years. (3) Predicated from the cyclical changing law that the annual precipitation decreases from high to low, the Horqin region will remain in a period of low precipitation between 2016 and 2020.

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“…Hydrological modelling has been widely used in numerous fields such as flood forecasting, water resource estimation, water project planning, groundwater level fluctuations, hydrological station planning, water quality monitoring and sediment load estimation [1][2][3][4][5][6][7][8][9][10]. At present, a significant goal of existing research efforts in hydrological modelling is to improve the accuracy of runoff simulation and prediction.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Influence of Rainfall Spatial Uncertainty on Hydrological Simulations Using the Bootstrap Method

Zhang

Shi

et al. 2018

Atmosphere

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Abstract:Rainfall stations of a certain number and spatial distribution supply sampling records of rainfall processes in a river basin. Uncertainty may be introduced when the station records are spatially interpolated for the purpose of hydrological simulations. This study adopts a bootstrap method to quantitatively estimate the uncertainty of areal rainfall estimates and its effects on hydrological simulations. The observed rainfall records are first analyzed using clustering and correlation methods and possible average basin rainfall amounts are calculated with a bootstrap method using various combinations of rainfall station subsets. Then, the uncertainty of simulated runoff, which is propagated through a hydrological model from the spatial uncertainty of rainfall estimates, is analyzed with the bootstrapped rainfall inputs. By comparing the uncertainties of rainfall and runoff, the responses of the hydrological simulation to the rainfall spatial uncertainty are discussed. Analyses are primarily performed for three rainfall events in the upstream of the Qingjian River basin, a sub-basin of the middle Yellow River; moreover, one rainfall event in the Longxi River basin is selected for the analysis of the areal representation of rainfall stations. Using the Digital Yellow River Integrated Model, the results show that the uncertainty of rainfall estimates derived from rainfall station network has a direct influence on model simulation, which can be conducive to better understand of rainfall spatial characteristic. The proposed method can be a guide to quantify an approximate range of simulated error caused by the spatial uncertainty of rainfall input and the quantified relationship between rainfall input and simulation performance can provide useful information about rainfall station network management in river basins.

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Modeling of groundwater level fluctuations using dendrochronology in alluvial aquifers

Cited by 225 publications

References 68 publications

Accuracy Evaluation of Two High-Resolution Satellite-Based Rainfall Products: TRMM 3B42V7 and CMORPH in Shanghai

Accuracy Evaluation of Two High-Resolution Satellite-Based Rainfall Products: TRMM 3B42V7 and CMORPH in Shanghai

Annual Precipitation Fluctuation and Spatial Differentiation Characteristics of the Horqin Region

Analysis of the Influence of Rainfall Spatial Uncertainty on Hydrological Simulations Using the Bootstrap Method

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