Effect of spatial variability and seasonality in soil moisture on drainage thresholds and fluxes in a conceptual hydrological model

2012 ◽  
Vol 26 (18) ◽  
pp. 2838-2844 ◽  
Author(s):  
H.K. McMillan
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Hydrological Model ◽  
Conceptual Hydrological Model

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.

The additional value of using proxy data besides runoff for calibrating a conceptual hydrological model in a small agricultural catchment

2020 ◽  
Author(s):  
Borbála Széles ◽  
Juraj Parajka ◽  
Patrick Hogan ◽  
Rasmiaditya Silasari ◽  
Lovrenc Pavlin ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Overland Flow ◽  
Hydrological Model ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Runoff Generation ◽  
Proxy Data ◽  
One Step ◽  
Additional Value ◽  
Conceptual Hydrological Model

<p>The aim of this study was to explore the additional value of using proxy data besides runoff for calibrating a conceptual hydrological model. The study area was the Hydrological Open Air Laboratory (HOAL), a 66 ha large experimental catchment in Austria. A conceptual, HBV type, spatially lumped hydrological model was calibrated following two approaches. First, the model was calibrated in one step using only runoff data. Second, we proposed a step-by-step approach, where the modules of the model (snow, soil moisture and runoff generation) were calibrated using proxy data besides runoff, such as snow, actual evapotranspiration, soil moisture, overland flow and groundwater level. The two approaches were evaluated on annual, seasonal and daily time scales. Using the proposed step-by-step approach, the runoff volume errors in the calibration and validation periods were 0% and -1%, the monthly Pearson correlation coefficients were 0.92 and 0.82, and the daily logarithmic Nash Sutcliffe efficiencies were 0.59 and 0.18, respectively. The additional benefit of using proxy data besides runoff was the improved overall process consistency compared to the approach when only runoff was used for model calibration. Soil moisture and evapotranspiration observations had the largest influence on simulated runoff, while the calibration of the snow and runoff generation modules had a smaller influence.</p>

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.

scholarly journals SHETRAN and HEC HMS Model Evaluation for Runoff and Soil Moisture Simulation in the Jičinka River Catchment (Czech Republic)

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 872
Author(s):  
Vesna Đukić ◽  
Ranka Erić
Keyword(s):  
Soil Moisture ◽  
Czech Republic ◽  
Hydrological Model ◽  
Flash Flood ◽  
Model Performance ◽  
Rainfall Runoff ◽  
The Czech Republic ◽  
River Catchment ◽  
Hydrological Variable ◽  
Model Structures

Due to the improvement of computation power, in recent decades considerable progress has been made in the development of complex hydrological models. On the other hand, simple conceptual models have also been advanced. Previous studies on rainfall–runoff models have shown that model performance depends very much on the model structure. The purpose of this study is to determine whether the use of a complex hydrological model leads to more accurate results or not and to analyze whether some model structures are more efficient than others. Different configurations of the two models of different complexity, the Système Hydrologique Européen TRANsport (SHETRAN) and Hydrologic Modeling System (HEC-HMS), were compared and evaluated in simulating flash flood runoff for the small (75.9 km2) Jičinka River catchment in the Czech Republic. The two models were compared with respect to runoff simulations at the catchment outlet and soil moisture simulations within the catchment. The results indicate that the more complex SHETRAN model outperforms the simpler HEC HMS model in case of runoff, but not for soil moisture. It can be concluded that the models with higher complexity do not necessarily provide better model performance, and that the reliability of hydrological model simulations can vary depending on the hydrological variable under consideration.

scholarly journals Effects of micro-topography and vegetation type on soil moisture in a large gully on the Loess Plateau of China

2017 ◽  
Vol 49 (4) ◽  
pp. 1255-1270 ◽  
Author(s):  
Bowei Yu ◽  
Gaohuan Liu ◽  
Qingsheng Liu ◽  
Jiuliang Feng ◽  
Xiaoping Wang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Loess Plateau ◽  
Root Zone ◽  
Plane Surface ◽  
Vegetation Type ◽  
Chinese Loess Plateau ◽  
Chinese Loess ◽  
Micro Topography ◽  
The Chinese Loess Plateau

Abstract Large gullies occur globally and can be classified into four main micro-topographic types: ridges, plane surfaces, pipes and cliffs. Afforestation is an effective method of controlling land degradation worldwide. However, the combined effects of afforestation and micro-topography on the variability of soil moisture remain poorly understood. The primary objectives of this study were to determine whether afforestation affects the spatial pattern of the root-zone (0–100 cm) soil moisture and whether soil moisture dynamics differ among the micro-topographic types in gully areas of the Chinese Loess Plateau. The results showed that in the woodland regions, the spatial mean moisture values decreased by an average of 6.2% and the spatial variability increased, as indicated by the standard deviation (17.1%) and the coefficient of variation (22.2%). In general, different micro-topographic types exerted different influences on soil moisture behavior. The plane surface presented the largest average soil moisture values and the smallest spatial variability. The lowest soil moisture values were observed in the ridge, mainly due to the rapid drainage of these areas. Although pipe woodland region can concentrate surface runoff during and after rainfall, the larger trees growing in these areas can lead to increased soil moisture evapotranspiration.

Statistical characterization of the spatial variability of soil moisture in a cutover peatland

2004 ◽  
Vol 18 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Richard M. Petrone ◽  
J. S. Price ◽  
S. K. Carey ◽  
J. M. Waddington
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Statistical Characterization

Spatial dynamics of soil moisture and temperature in a black spruce boreal chronosequence

2006 ◽  
Vol 36 (11) ◽  
pp. 2794-2802 ◽  
Author(s):  
Ben Bond-Lamberty ◽  
Karen M Brown ◽  
Carol Goranson ◽  
Stith T Gower
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Sampling Design ◽  
Black Spruce ◽  
Structural Characteristics ◽  
Spatial Dynamics ◽  
Spherical Model ◽  
Local Scale ◽  
Spatial Dependencies ◽  
The Mean

This study analyzed the spatial dependencies of soil moisture and temperature in a six-stand chronosequence of boreal black spruce (Picea mariana (Mill.) BSP) stands. Spatial variability of soil temperature (TSOIL) was evaluated twice during the growing season using four transects in each stand, employing a cyclic sampling design with measurements spaced 2–92 m apart. Soil moisture (θg) was measured on one occasion. A spherical model was used to analyze the geostatistical correlation structure; θg and TSOIL at the 7- and 21-year-old stands did not exhibit stable ranges or sills. The fits with stable ranges and sills modeled the spatial patterns in the older stands reasonably well, although unexplained variability was high. Calculated ranges varied from 3 to 150 m for these stands, lengths probably related to structural characteristics influential in local-scale energy transfer. Transect-to-transect variability was significant and typically 5%–15% of the mean for TSOIL and 10%–70% for θg. TSOIL and θg were negatively correlated for most stands and depths, with TSOIL dropping 0.5–0.9 °C for every 1% rise in θg. The results reported here provide initial data to assess the spatial variability of TSOIL and θg in a variety of boreal forest stand ages.

scholarly journals Spatial variability and its scale dependency of observed and modeled soil moisture over different climate regions

2013 ◽  
Vol 17 (3) ◽  
pp. 1177-1188 ◽  
Author(s):  
B. Li ◽  
M. Rodell
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Land Surface ◽  
Large Scale ◽  
Warm Season ◽  
Scale Dependency ◽  
Convex Shape ◽  
Spatial Moments ◽  
Environmental Controls

Abstract. Past studies on soil moisture spatial variability have been mainly conducted at catchment scales where soil moisture is often sampled over a short time period; as a result, the observed soil moisture often exhibited smaller dynamic ranges, which prevented the complete revelation of soil moisture spatial variability as a function of mean soil moisture. In this study, spatial statistics (mean, spatial variability and skewness) of in situ soil moisture, modeled and satellite-retrieved soil moisture obtained in a warm season (198 days) were examined over three large climate regions in the US. The study found that spatial moments of in situ measurements strongly depend on climates, with distinct mean, spatial variability and skewness observed in each climate zone. In addition, an upward convex shape, which was revealed in several smaller scale studies, was observed for the relationship between spatial variability of in situ soil moisture and its spatial mean when statistics from dry, intermediate, and wet climates were combined. This upward convex shape was vaguely or partially observable in modeled and satellite-retrieved soil moisture estimates due to their smaller dynamic ranges. Despite different environmental controls on large-scale soil moisture spatial variability, the correlation between spatial variability and mean soil moisture remained similar to that observed at small scales, which is attributed to the boundedness of soil moisture. From the smaller support (effective area or volume represented by a measurement or estimate) to larger ones, soil moisture spatial variability decreased in each climate region. The scale dependency of spatial variability all followed the power law, but data with large supports showed stronger scale dependency than those with smaller supports. The scale dependency of soil moisture variability also varied with climates, which may be linked to the scale dependency of precipitation spatial variability. Influences of environmental controls on soil moisture spatial variability at large scales are discussed. The results of this study should be useful for diagnosing large scale soil moisture estimates and for improving the estimation of land surface processes.

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