Identify the influencing paths of precipitation and soil water storage on runoff: an example from Xinjiang River Basin, Poyang Lake, China

2017 ◽  
Vol 18 (5) ◽  
pp. 1598-1605
Author(s):  
Hongxiang Fan ◽  
Ligang Xu ◽  
Xiaolong Wang ◽  
Yuexia Wu ◽  
Jiahu Jiang
Keyword(s):  
Soil Water ◽  
River Basin ◽  
Poyang Lake ◽  
Water Storage ◽  
Soil Water Storage ◽  
Hydrological Process ◽  
Analysis Method ◽  
Runoff Generation ◽  
The Past ◽  
Total Influence

Abstract Runoff generation is a complex meteorological-hydrological process influenced by many factors. We analyzed the effects of changes in precipitation and soil water storage (SWS) on runoff generation using the path-analysis method (PAM) in Xinjiang River Basin (XJRB). By using multiple trend analysis we found that precipitation, SWS and runoff in XJRB fluctuated throughout the past 30 years with no monotonic trends at both annual and seasonal scales. Further analysis demonstrated that runoff is more sensitive to precipitation than to SWS in XJRB. PAM results showed that direct influence of precipitation on runoff was seven times as large as that of SWS. Moreover, the indirect influence of precipitation on runoff through SWS accounts for 11–31% of the total influence of precipitation on runoff. This information will improve the description of precipitation and runoff relationship as well as the planning and management of water resources.

scholarly journals Runoff generation dynamics within a humid river basin

2008 ◽  
Vol 8 (6) ◽  
pp. 1349-1357 ◽  
Author(s):  
S. Manfreda
Keyword(s):  
Water Balance ◽  
Soil Water ◽  
River Basin ◽  
Parameters Estimation ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
Runoff Generation ◽  
Water Storage Capacity ◽  
Soil Water Storage Capacity ◽  
Runoff Production

Abstract. The present paper introduces an analytical approach for the description of the soil water balance and runoff production within a schematic river basin. The model is based on a stochastic differential equation where the rainfall is interpreted as an additive noise in the soil water balance and is assumed uniform over the basin, the basin heterogeneity is characterized by a parabolic distribution of the soil water storage capacity and the runoff production occurs for saturation excess. The model allowed to derive the probability density function of the produced surface runoff highlighting the role played by climate and physical characteristics of a basin on runoff dynamics. Finally, the model have been tested over a humid basin of Southern Italy proposing also a strategy for the parameters estimation.

scholarly journals Rainfall–Runoff Processes and Modelling in Regions Characterized by Deficiency in Soil Water Storage

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1858
Author(s):  
Pengfei Shi ◽  
Tao Yang ◽  
Chong-Yu Xu ◽  
Bin Yong ◽  
Ching-Sheng Huang ◽  
...  
Keyword(s):  
Soil Water ◽  
Storage Capacity ◽  
Layer Structure ◽  
Water Storage ◽  
Soil Water Storage ◽  
Runoff Generation ◽  
Xinanjiang Model ◽  
Water Storage Capacity ◽  
Variable Threshold ◽  
Soil Water Storage Capacity

The partial runoff is complicated in semi-arid and some semi-humid zones in terms of what the runoff generates in partial vertical positions. The partial runoff is highlighted by horizontal soil heterogeneity as well. How to identify the partial runoff and develop a variable threshold for runoff generation is a great difficulty and challenge. In this work, the partial runoff is identified by using a variable active runoff layer structure, and a variable soil water storage capacity is proposed to act as a threshold for runoff generation. A variable layer-based runoff model (VLRM) for simulating the complex partial runoff was therefore developed, using dual distribution curves for variable soil water storage capacity over basin. The VLRM is distinct in that the threshold for runoff generation is denoted by variable soil water storage capacity instead of infiltration capacity or constant soil water storage capacity. A series of flood events in two typical basins of North China are simulated by the model, and also by the Xinanjiang model. Results demonstrate that the new threshold performs well and the new model outperforms the Xinanjiang model. The approach improves current hydrological modelling for complex runoff in regions with large deficiencies in soil water storage.

scholarly journals Regression Models for Soil Water Storage Estimation Using the ESA CCI Satellite Soil Moisture Product: A Case Study in Northeast Portugal

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Tomás de Figueiredo ◽  
Ana Caroline Royer ◽  
Felícia Fonseca ◽  
Fabiana Costa de Araújo Schütz ◽  
Zulimar Hernández
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Regression Models ◽  
Meteorological Data ◽  
Water Storage ◽  
Model Performance ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
The Relationship

The European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.

scholarly journals Energy balance closure on a winter wheat stand: comparing the eddy covariance technique with the soil water balance method

2016 ◽  
Vol 13 (1) ◽  
pp. 63-75 ◽  
Author(s):  
K. Imukova ◽  
J. Ingwersen ◽  
M. Hevart ◽  
T. Streck
Keyword(s):  
Energy Balance ◽  
Water Balance ◽  
Winter Wheat ◽  
Water Content ◽  
Soil Water ◽  
Water Storage ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
Water Balance Method ◽  
Closure Method

Abstract. The energy balance of eddy covariance (EC) flux data is typically not closed. The nature of the gap is usually not known, which hampers using EC data to parameterize and test models. In the present study we cross-checked the evapotranspiration data obtained with the EC method (ETEC) against ET rates measured with the soil water balance method (ETWB) at winter wheat stands in southwest Germany. During the growing seasons 2012 and 2013, we continuously measured, in a half-hourly resolution, latent heat (LE) and sensible (H) heat fluxes using the EC technique. Measured fluxes were adjusted with either the Bowen-ratio (BR), H or LE post-closure method. ETWB was estimated based on rainfall, seepage and soil water storage measurements. The soil water storage term was determined at sixteen locations within the footprint of an EC station, by measuring the soil water content down to a soil depth of 1.5 m. In the second year, the volumetric soil water content was additionally continuously measured in 15 min resolution in 10 cm intervals down to 90 cm depth with sixteen capacitance soil moisture sensors. During the 2012 growing season, the H post-closed LE flux data (ETEC =  3.4 ± 0.6 mm day−1) corresponded closest with the result of the WB method (3.3 ± 0.3 mm day−1). ETEC adjusted by the BR (4.1 ± 0.6 mm day−1) or LE (4.9 ± 0.9 mm day−1) post-closure method were higher than the ETWB by 24 and 48 %, respectively. In 2013, ETWB was in best agreement with ETEC adjusted with the H post-closure method during the periods with low amount of rain and seepage. During these periods the BR and LE post-closure methods overestimated ET by about 46 and 70 %, respectively. During a period with high and frequent rainfalls, ETWB was in-between ETEC adjusted by H and BR post-closure methods. We conclude that, at most observation periods on our site, LE is not a major component of the energy balance gap. Our results indicate that the energy balance gap is made up by other energy fluxes and unconsidered or biased energy storage terms.

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