Using DEM to quantify spatial variability of soil storage capacity: a semi-distributed hydrological model for Northern China

2005 ◽  
Author(s):  
Zhao Qiang ◽  
Gong Huili ◽  
Deng Wei ◽  
Wang Shangyi ◽  
ZhaoWenji ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Hydrological Model ◽  
Storage Capacity ◽  
Northern China ◽  
Distributed Hydrological Model ◽  
Soil Storage ◽  
Soil Storage Capacity

Small soil storage capacity limits benefit of winter snowpack to upland vegetation

2011 ◽  
Vol 25 (25) ◽  
pp. 3858-3865 ◽  
Author(s):  
T. J. Smith ◽  
J. P. McNamara ◽  
A. N. Flores ◽  
M. M. Gribb ◽  
P. S. Aishlin ◽  
...  
Keyword(s):  
Storage Capacity ◽  
Capacity Limits ◽  
Soil Storage ◽  
Soil Storage Capacity

scholarly journals Effect of spatial distribution of daily rainfall on interior catchment response of a distributed hydrological model

2006 ◽  
Vol 3 (4) ◽  
pp. 2175-2208 ◽  
Author(s):  
J. M. Schuurmans ◽  
M. F. P. Bierkens
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Groundwater Level ◽  
Hydrological Model ◽  
Daily Rainfall ◽  
Radar Data ◽  
Distributed Hydrological Model ◽  
Average Rainfall ◽  
Hydrological System ◽  
Insight Into

Abstract. We investigate the effect of spatial variability of daily rainfall on soil moisture, groundwater level and discharge using a physically-based, fully-distributed hydrological model. We focus on the effect of rainfall spatial variability on day-to-day variability of the interior catchment response, as well as on its effect on the general hydrological behavior of the catchment. The study is performed in a flat rural catchment (135 km2) in The Netherlands, where climate is semi-humid (average precipitation 800 mm/year, evapotranspiration 550 mm/year) and rainfall is predominantly stratiform. Both range-corrected radar data (resolution 2.5×2.5 km2) as well as data from a dense network of 30 raingauges are used, observed for the period March–October 2004. Eight different rainfall scenarios, either spatially distributed or spatially uniform, are used as input for the hydrological model. The main conclusions from this study are: (i) using a single raingauge as rainfall input carries a great risk for the prediction of discharge, groundwater level and soil moisture, especially if the raingauge is situated outside the catchment; (ii) taking into account the spatial variability of rainfall instead of using areal average rainfall as input for the model is needed to get insight into the day-to-day spatial variability of discharge, groundwater level and soil moisture content; (iii) to get insight into the general behavior of the hydrological system it is sufficient to use correct predictions of areal average rainfall over the catchment.

scholarly journals Understanding dominant controls on streamflow spatial variability to set up a semi-distributed hydrological model: the case study of the Thur catchment

2020 ◽  
Vol 24 (3) ◽  
pp. 1319-1345
Author(s):  
Marco Dal Molin ◽  
Mario Schirmer ◽  
Massimiliano Zappa ◽  
Fabrizio Fenicia
Keyword(s):  
Spatial Variability ◽  
Model Building ◽  
Hydrological Model ◽  
Previous Analysis ◽  
Seasonal Patterns ◽  
Distributed Hydrological Model ◽  
Second Stage ◽  
Set Up ◽  
Predictions In Ungauged Basins

Abstract. This study documents the development of a semi-distributed hydrological model aimed at reflecting the dominant controls on observed streamflow spatial variability. The process is presented through the case study of the Thur catchment (Switzerland, 1702 km2), an alpine and pre-alpine catchment where streamflow (measured at 10 subcatchments) has different spatial characteristics in terms of amounts, seasonal patterns, and dominance of baseflow. In order to appraise the dominant controls on streamflow spatial variability and build a model that reflects them, we follow a two-stage approach. In a first stage, we identify the main climatic or landscape properties that control the spatial variability of streamflow signatures. This stage is based on correlation analysis, complemented by expert judgement to identify the most plausible cause–effect relationships. In a second stage, the results of the previous analysis are used to develop a set of model experiments aimed at determining an appropriate model representation of the Thur catchment. These experiments confirm that only a hydrological model that accounts for the heterogeneity of precipitation, snow-related processes, and landscape features such as geology produces hydrographs that have signatures similar to the observed ones. This model provides consistent results in space–time validation, which is promising for predictions in ungauged basins. The presented methodology for model building can be transferred to other case studies, since the data used in this work (meteorological variables, streamflow, morphology, and geology maps) are available in numerous regions around the globe.

scholarly journals A distributed Grid-Xinanjiang model with integration of subgrid variability of soil storage capacity

2016 ◽  
Vol 9 (2) ◽  
pp. 97-105 ◽  
Author(s):  
Wei-jian Guo ◽  
Chuan-hai Wang ◽  
Teng-fei Ma ◽  
Xian-min Zeng ◽  
Hai Yang
Keyword(s):  
Storage Capacity ◽  
Xinanjiang Model ◽  
Soil Storage ◽  
Soil Storage Capacity

scholarly journals Exploring the role of soil storage capacity for explaining deviations from the Budyko curve using a simple water balance model

2021 ◽  
Author(s):  
Jan Bondy ◽  
Jan Wienhöfer ◽  
Laurent Pfister ◽  
Erwin Zehe
Keyword(s):  
Water Balance ◽  
Storage Capacity ◽  
Field Capacity ◽  
Water Balance Model ◽  
Balance Model ◽  
Joint Control ◽  
Soil Storage ◽  
Wide Range ◽  
Evaporation Ratio ◽  
Soil Storage Capacity

Abstract. The Budyko curve is a widely used framework for predicting the steady-state water balance –solely based on the hydro-climatic setting of river basins. While this framework has been tested and verified across a wide range of climates and settings around the globe, numerous catchments have been reported to considerably deviate from the predicted behavior. Here, we hypothesize that storage capacity and field capacity of the root zone are important controls of the water limitation of evapotranspiration and thus deviations of the mean annual water balance from the Budyko curve. For testing our hypothesis, we selected 16 catchments of different climatic settings and varied the corresponding parameters of a simple water balance model that was previously calibrated against long-term data and investigated the corresponding variations of the simulated water balance in the Budyko space. We found that total soil storage capacity –by controlling water availability and limitation of evapotranspiration– explains deviations of the evaporation ratio (EVR) from the Budyko curve. Similarly, however to a lesser extent, the evaporation ratio showed sensitivity to alterations of the field capacity. In most cases, the parameter variations generated evaporation ratios enveloping the Budyko curve. The distinct soil storage volumes that matched the Budyko curve clustered at a normalized storage capacity equivalent to 5–15 % of mean annual precipitation. The second, capillarity-related soil parameter clustered at around 0.6–0.8, which is in line with its hydropedological interpretation. A simultaneous variation of both parameters provided additional insights into the interrelation of both parameters and their joint control on offsets from the Budyko curve. Here we found three different sensitivity patterns and we conclude the study with a reflection relating these offsets to the concept of catchment coevolution. The results of this study could also be useful to facilitate evaluation of the water balance in data-scarce regions, as they help constrain parameterizations for hydrological models a priori using the Budyko curve as a predictor.

scholarly journals Effect of spatial distribution of daily rainfall on interior catchment response of a distributed hydrological model

2007 ◽  
Vol 11 (2) ◽  
pp. 677-693 ◽  
Author(s):  
J. M. Schuurmans ◽  
M. F. P. Bierkens
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Groundwater Level ◽  
Large Scale ◽  
Hydrological Model ◽  
Daily Rainfall ◽  
Distributed Hydrological Model ◽  
General Behaviour ◽  
Average Rainfall ◽  
Insight Into

Abstract. We investigate the effect of spatial variability of daily rainfall on soil moisture, groundwater level and discharge using a physically-based, fully-distributed hydrological model. This model is currently in use with the district water board and is considered to represent reality. We focus on the effect of rainfall spatial variability on day-to-day variability of the interior catchment response, as well as on its effect on the general hydrological behaviour of the catchment. The study is performed in a flat rural catchment (135 km2) in the Netherlands, where the climate is semi-humid (average precipitation 800 mm/year, evapotranspiration 550 mm/year) and rainfall is predominantly stratiform (i.e. large scale). Both range-corrected radar data (resolution 2.5×2.5 km2) as well as data from a dense network of 30 raingauges are used, observed for the period March–October 2004. Eight different rainfall scenarios, either spatially distributed or spatially uniform, are used as input for the hydrological model. The main conclusions from this study are: (i) using a single raingauge as rainfall input carries a great risk for the prediction of discharge, groundwater level and soil moisture, especially if the raingauge is situated outside the catchment; (ii) taking into account the spatial variability of rainfall instead of using areal average rainfall as input for the model is needed to get insight into the day-to-day spatial variability of discharge, groundwater level and soil moisture content; (iii) to get insight into the general behaviour of the hydrological system it is sufficient to use correct predictions of areal average rainfall over the catchment.

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