scholarly journals Derivation of the Spatial Distribution of Free Water Storage Capacity Based on Topographic Index

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1407
Author(s):  
Bingxing Tong ◽  
Zhijia Li ◽  
Cheng Yao ◽  
Jingfeng Wang ◽  
Yingchun Huang
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Land Surface ◽  
Storage Capacity ◽  
Water Storage ◽  
Free Water ◽  
Flood Events ◽  
Runoff Generation ◽  
Topographic Index ◽  
Water Storage Capacity

Free water storage capacity, an important characteristic of land surface related to runoff process, has a significant influence on runoff generation and separation. It is thus necessary to derive reasonable spatial distribution of free water storage capacity for rainfall-runoff simulation, especially in distributed modeling. In this paper, a topographic index based approach is proposed for the derivation of free water storage capacity spatial distribution. The topographic index, which can be obtained from digital elevation model (DEM), are used to establish a functional relationship with free water storage capacity in the proposed approach. In this case, the spatial variability of free water storage capacity can be directly estimated from the characteristics of watershed topography. This approach was tested at two medium sized watersheds, including Changhua and Chenhe, with the drainage areas of 905 km2 and 1395 km2, respectively. The results show that locations with larger values of free water storage capacity generally correspond to locations with higher topographic index values, such as riparian region. The estimated spatial distribution of free water storage capacity is also used in a distributed, grid-based Xinanjiang model to simulate 10 flood events for Chenhe Watershed and 17 flood events for Changhua Watershed. Our analysis indicates that the proposed approach based on topographic index can produce reasonable spatial variability of free water storage capacity and is more suitable for flood simulation.

scholarly journals A method to obtain the spatial distribution of free water storage capacity based on topo-graphic index

2017 ◽  
Vol 29 (5) ◽  
pp. 1238-1244
Author(s):  
TONG Bingxing ◽  
◽  
YAO Cheng ◽  
LI Zhijia ◽  
HUANG Xiaoxiang
Keyword(s):  
Spatial Distribution ◽  
Storage Capacity ◽  
Water Storage ◽  
Free Water ◽  
Water Storage Capacity

scholarly journals The Influence of a Prolonged Meteorological Drought on the Catchment Water Storage Capacity: A Hydrological Model Perspective

2020 ◽  
Author(s):  
Zhengke Pan ◽  
Pan Liu ◽  
Chongyu Xu ◽  
Lei Cheng ◽  
Jing Tian ◽  
...  
Keyword(s):  
Change Point ◽  
Storage Capacity ◽  
Critical Role ◽  
Time Lag ◽  
Water Storage ◽  
Meteorological Drought ◽  
Change Point Analysis ◽  
Runoff Generation ◽  
Broadleaf Forest ◽  
Water Storage Capacity

Abstract. Understanding the propagation process of prolonged meteorological droughts (i.e., decade) helps solve the problem of increasing water scarcity around the world. Historical literature studied the propagation between different drought types (e.g., from meteorological to hydrological drought) with mainly statistical approaches, however, little attention has been paid to the causality between the meteorological drought with potential changes in the Catchment Water Storage Capacity (CWSC) where the latter plays a critical role in catchment response behavior to former. This study used the temporal variation in the estimated value of a model parameter that denotes the CWSC in its model structure to reflect the potential changes in real CWSC. The most likely Change points of the CWSC were determined based on the Bayesian Change point analysis. Also, the possible association and linkage between the shift in the CWSC and the time-lag of the catchment (i.e., time-lag between the occurrence of the drought with the Change point) with multiple catchment properties and climate characteristics have been studied. Catchments from southeastern Australia were used as a study area to verify the effectiveness of the proposed approach. Results indicated that (1) in 62.7 % of the catchments, the sustained drought causes significant shifts in the CWSC. The shift led to the opposite response in two subsets of catchments, i.e., 48.2 % of catchments had lower runoff generation rates for a given rainfall while 14.5 % of catchments had higher runoff generation rate. (2) Catchments with larger elevation and slope, lower forest coverage of Evergreen Broadleaf Forest are more likely to have increase in the CWSC during a chronic drought while smaller catchments with lower elevation, lower coverage of the Evergreen Broadleaf Forest are more likely to have a decrease in the CWSC. (3) The changed catchments were not equally susceptible to the pressure due to persistent meteorological drought. Catchments with a lower proportion of Evergreen Broadleaf Forest usually have longer time-lag and are more resilient. This study improves our understanding of possible changes in CWSC induced by a prolonged meteorological drought, which will help improve our ability to simulate the hydrological system.

scholarly journals The influence of a prolonged meteorological drought on catchment water storage capacity: a hydrological-model perspective

2020 ◽  
Vol 24 (9) ◽  
pp. 4369-4387
Author(s):  
Zhengke Pan ◽  
Pan Liu ◽  
Chong-Yu Xu ◽  
Lei Cheng ◽  
Jing Tian ◽  
...  
Keyword(s):  
Change Point ◽  
Hydrological Model ◽  
Storage Capacity ◽  
Time Lag ◽  
Water Storage ◽  
Meteorological Drought ◽  
Model Parameters ◽  
Runoff Generation ◽  
Broadleaf Forest ◽  
Water Storage Capacity

Abstract. Understanding the propagation of prolonged meteorological drought helps solve the problem of intensified water scarcity around the world. Most of the existing literature studied the propagation of drought from one type to another (e.g., from meteorological to hydrological drought) with statistical approaches; there remains difficulty in revealing the causality between meteorological drought and potential changes in the catchment water storage capacity (CWSC). This study aims to identify the response of the CWSC to the meteorological drought by examining the changes of hydrological-model parameters after drought events. Firstly, the temporal variation of a model parameter that denotes that the CWSC is estimated to reflect the potential changes in the real CWSC. Next, the change points of the CWSC parameter were determined based on the Bayesian change point analysis. Finally, the possible association and linkage between the shift in the CWSC and the time lag of the catchment (i.e., time lag between the onset of the drought and the change point) with multiple catchment properties and climate characteristics were identified. A total of 83 catchments from southeastern Australia were selected as the study areas. Results indicated that (1) significant shifts in the CWSC can be observed in 62.7 % of the catchments, which can be divided into two subgroups with the opposite response, i.e., 48.2 % of catchments had lower runoff generation rates, while 14.5 % of catchments had higher runoff generation rate; (2) the increase in the CWSC during a chronic drought can be observed in smaller catchments with lower elevation, slope and forest coverage of evergreen broadleaf forest, while the decrease in the CWSC can be observed in larger catchments with higher elevation and larger coverage of evergreen broadleaf forest; (3) catchments with a lower proportion of evergreen broadleaf forest usually have a longer time lag and are more resilient. This study improves our understanding of possible changes in the CWSC induced by a prolonged meteorological drought, which will help improve our ability to simulate the hydrological system under climate change.

scholarly journals Large-scale runoff generation – parsimonious parameterisation using high-resolution topography

2010 ◽  
Vol 7 (5) ◽  
pp. 6613-6646
Author(s):  
L. Gong ◽  
S. Halldin ◽  
C.-Y. Xu
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Storage Capacity ◽  
Hydrological Models ◽  
Runoff Generation ◽  
Model Framework ◽  
Topographic Index ◽  
Topographic Analysis ◽  
Generation Algorithm ◽  
Water Storage Capacity

Abstract. World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting a very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TGR only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3'' (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

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 Global distribution of the rooting zone water storage capacity reflects plant adaptation to the environment

2021 ◽  
Author(s):  
Benjamin D. Stocker ◽  
Shersingh Joseph Tumber-Dávila ◽  
Alexandra G. Konings ◽  
Martha B. Anderson ◽  
Christopher Hain ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Storage Capacity ◽  
Water Storage ◽  
Spatial Variations ◽  
Rooting Depth ◽  
Water Storage Capacity ◽  
Rooting Zone ◽  
Vegetation Activity ◽  
Zone Water

AbstractThe rooting zone water storage capacity (S0) extends from the soil surface to the weathered bedrock (the Critical Zone) and determines land-atmosphere exchange during dry periods. Despite its importance to land-surface modeling, variations of S0 across space are largely unknown as they cannot be observed directly. We developed a method to diagnose global variations of S0 from the relationship between vegetation activity (measured by sun-induced fluorescence and by the evaporative fraction) and the cumulative water deficit (CWD). We then show that spatial variations in S0 can be predicted from the assumption that plants are adapted to sustain CWD extremes occurring with a return period that is related to the life form of dominant plants and the large-scale topographical setting. Predicted biome-level S0 distributions, translated to an apparent rooting depth (zr) by accounting for soil texture, are consistent with observations from a comprehensive zr dataset. Large spatial variations in S0 across the globe reflect adaptation of zr to the hydroclimate and topography and implies large heterogeneity in the sensitivity of vegetation activity to drought. The magnitude of S0 inferred for most of the Earth’s vegetated regions and particularly for those with a large seasonality in their hydroclimate indicates an important role for plant access to water stored at depth - beyond the soil layers commonly considered in land-surface models.

scholarly journals Large-scale runoff generation – parsimonious parameterisation using high-resolution topography

2011 ◽  
Vol 15 (8) ◽  
pp. 2481-2494 ◽  
Author(s):  
L. Gong ◽  
S. Halldin ◽  
C.-Y. Xu
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Storage Capacity ◽  
Hydrological Models ◽  
Runoff Generation ◽  
Model Framework ◽  
Topographic Index ◽  
Topographic Analysis ◽  
Generation Algorithm ◽  
Water Storage Capacity

Abstract. World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3" (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

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