scholarly journals Event Based Post-Fire Hydrological Modeling of the Upper Arroyo Seco Watershed in Southern California

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2303
Author(s):  
Nawa Raj Pradhan ◽  
Ian Floyd
Keyword(s):  
Southern California ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Rainfall Event ◽  
Watershed Model ◽  
Fire Event ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Rainfall Events ◽  
Event Based

Understanding, development and integration of pre-fire and post-fire watershed hydrological processes into a watershed hydrological model in a wild-fire repeating region similar to parts of California is critical for emergency assessments. 95% of the upper Arroyo Seco watershed located in Los Angeles County in southern California was burned by the Station fire that occurred in August 2009, significantly increasing the watershed observed runoff. This watershed was employed to develop the January 2008 rainfall runoff model as a pre-fire event-based watershed hydrological model. This pre-fire watershed model was subsequently employed in the rainfall events of 18 January 2010 and 27 February 2010, a few months after the fire event of August 2009. The pre-fire watershed model when employed in the post-fire rainfall events without considering the fire effects vastly underestimated the simulated discharge. For this reason, in this study of the post-fire catchment runoff modeling the following points are taken into consideration: (a) a realistic distributed initial soil moisture condition; (b) a formulation that includes a reduction factor and a burn severity factor, as multiplying factors to soil hydraulic conductivity in the soil characteristic curve; and (c) runoff routing parameterization under burned conditions. Developing the post-fire Arroyo Seco watershed model by using the above-mentioned points enhanced the Nash–Sutcliffe Efficiency from −24% to 82% for the 18 January 2010 rainfall event and from −47% to 96% for the 27 February 2010 rainfall event.

scholarly journals Application of the SCS–CN Method to the Hancheon Basin on the Volcanic Jeju Island, Korea

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3350
Author(s):  
Minseok Kang ◽  
Chulsang Yoo
Keyword(s):  
Negative Correlation ◽  
The Other ◽  
Jeju Island ◽  
Antecedent Soil Moisture ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Rainfall Events ◽  
Initial Abstraction ◽  
Other Hand ◽  
Scs Cn

This study investigates three issues regarding the application of the SCS–CN (Soil Conservation Service–Curve Number) method to a basin on the volcanic Jeju Island, Korea. The first issue is the possible relation between the initial abstraction and the maximum potential retention. The second is the determination of the maximum potential retention, which is also closely related to the estimation of CN. The third issue is the effect of the antecedent soil moisture condition (AMC) on the initial abstraction, maximum potential retention and CN. All of these issues are dealt with based on the analysis of several rainfall events observed in the Hancheon basin, a typical basin on Jeju Island. In summary, the results are that, firstly, estimates of initial abstraction, ratio λ, maximum potential retention, and CN were all found to be consistent with the SCS–CN model structure. That is, CN and the maximum potential retention showed a strong negative correlation, and the ratio λ and the maximum potential retention also showed a rather weak negative correlation. On the other hand, a significant positive correlation was found between CN and the ratio λ. Second, in the case where the accumulated number of days is four or five, the effect of antecedent precipitation amount is clear. The antecedent five-day rainfall amount for the AMC-III condition is higher than 400 mm, compared to the AMC-I condition of less than 100 mm. Third, an inverse proportional relationship is found between the AMC and the maximum potential retention. On the other hand, a clear linear proportional relation is found between the AMC and CN. Finally, the maximum potential retention for the Hancheon basin is around 200 mm, with the corresponding CN being around 65. The ratio between the initial abstraction and the maximum potential retention is around 0.3. Even though these results are derived by analyzing a limited number of rainfall events, they are believed to properly consider the soil characteristics of Jeju Island.

scholarly journals An Analytical Hydrological Model for the Study of Scaling Issues in Land Surface Modeling

2006 ◽  
Vol 10 (20) ◽  
pp. 1-24 ◽  
Author(s):  
Diandong Ren ◽  
Ann Henderson-Sellers
Keyword(s):  
Soil Moisture ◽  
Steady State ◽  
Analytical Model ◽  
Hydrological Model ◽  
Clay Soil ◽  
Initial Conditions ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Initial Soil Moisture ◽  
Initial Soil

Abstract Besides the atmospheric forcing such as solar radiation input and precipitation, the heterogeneity of the surface cover also plays an important role, especially in the distribution characteristics of the latent heat flux (LE). In this study, scaling issues are discussed based on an analytical hydrological model that describes the transpiration and diffusion processes of soil water. The solution of this analytical model is composed of a transient part that depends primarily on initial conditions and a steady part that depends on the boundary conditions. To know how sensitive the different averaging approaches are to the initial conditions, three initial profiles are chosen that cover the prevailing soil moisture regimes. After analyzing its solution, the study shows that 1) upon reaching the steady state, directly taking an average of soil properties will cause systematic overestimation in the calculation of area-averaged LE. For an initially very dry condition, averaging of a sandy soil and a clay soil can cause a percentage error as large as 40%. 2) For vegetation growing on sandy soils, a direct averaging of the transpiration rate results in persistent overestimation of LE. For vegetation growing on clay soil, however, even after reaching the steady state, averaging of two water extraction weights can be either an overestimation or an underestimation, depending on which two vegetation types are involved. 3) During the interim stage of drying down, averaging of the soil/vegetation properties can lead to either an overestimation or an underestimation, depending on the evolving stage of the soil moisture profile. 4) The initial soil moisture condition matters during the transient stage of drying down. Different initial soil moisture conditions yield different scenarios of underestimation and overestimation patterns and a differing severity of errors. The simplicity of the analytical model and the heuristic initial soil profiles make the generalization easier than using sophisticated numerical models and make the causality mechanism clearer for physical interpretations.

Large Scale Basins With Small to Negligible Slopes

2000 ◽  
Vol 31 (1) ◽  
pp. 27-40 ◽  
Author(s):  
Luis Silveira
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Hydrological Model ◽  
Transport Processes ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Soil Moisture Storage ◽  
High Soil Moisture ◽  
Rio Negro ◽  
Moisture Storage

Large basins with small to negligible slopes are seldom considered in the hydrological literature. An example of such basins is the Río Negro catchment in Uruguay. The first of this two-paper series showed the following special features: a) the existence of strongly developed horizontal layers and an essentially impervious B-horizon, b) significantly high soil moisture storage in terms of normally expected rainfall during a storm and c) the importance of vertical water transport processes to establish the soil moisture condition prior to a storm and its role concerning basin runoff response. These observations and hypotheses were taken into account by the lumped conceptual hydrological model called Hidro-Urfing through the percolation function and the basin runoff response function. This second paper shows its application to the Laguna I basin, a sub-basin of the Río Negro catchment with a surface area of 13,945 km2, and its ability to model the major storm hydrographs without any subdivision into smaller sub-basins. Modelling of low flows requires disaggregation of spatial-scale issues. A hydrological model of the entire Río Negro catchment did not previously exist.

ANALYSIS OF SUCTION DISTRIBUTION RESPONSE TO RAINFALL EVENT AND TREE CANOPY

2016 ◽  
Vol 78 (8-5) ◽  
Author(s):  
Mohd FakhrurazziIshak ◽  
Nazri Ali ◽  
Azman Kassim
Keyword(s):  
Matric Suction ◽  
Field Monitoring ◽  
Rainfall Event ◽  
Tree Canopy ◽  
Dominant Factor ◽  
Residual Soil ◽  
Initial Condition ◽  
Canopy Interception ◽  
Rainfall Events ◽  
Sloping Surface

This study provides an exploration of matric suction influenced by tree canopy interception on a single rainfall event. A field monitoring was carried out to measure matric suction at slope with two conditions; at toe of slope without tree and with a tree at toe of slope on a tropical residual soil. The variation in matric suction values and matric suction profiles response to the rainfall events on slope with and without a tree at toe were analysed to reveal the effect of the tree canopy. At initial condition, the matric suction was significantly higher at vicinity of tree compared to that of area without tree at toe of slope. However, a typical short and intense tropical rainfall has caused the matric suction to drop dramatically to a minimum value on slope without tree. This condition did not occur on slope with tree. Although, both slopes (with and without tree at toe) received the same amount of precipitation rainfall but the different responses in matric suction valueswere clearly shown at slope with tree at the slope toe. The short and intense rainfalls appeared to be the dominant factor to the suction variation at slope without tree, but not at slope with the tree. The tree canopy can be a factor to influence the suction variation at slope with tree as canopy interception reduced the amount of precipitation to the ground/sloping surface

scholarly journals Benefits and limitations of data assimilation for discharge forecasting using an event-based rainfall–runoff model

2013 ◽  
Vol 13 (3) ◽  
pp. 583-596 ◽  
Author(s):  
M. Coustau ◽  
S. Ricci ◽  
V. Borrell-Estupina ◽  
C. Bouvier ◽  
O. Thual
Keyword(s):  
Data Assimilation ◽  
Hydrological Model ◽  
Peak Discharge ◽  
State Variables ◽  
Rainfall Runoff ◽  
Discharge Data ◽  
Southern France ◽  
Flood Peak ◽  
Event Based ◽  
The Impact

Abstract. Mediterranean catchments in southern France are threatened by potentially devastating fast floods which are difficult to anticipate. In order to improve the skill of rainfall-runoff models in predicting such flash floods, hydrologists use data assimilation techniques to provide real-time updates of the model using observational data. This approach seeks to reduce the uncertainties present in different components of the hydrological model (forcing, parameters or state variables) in order to minimize the error in simulated discharges. This article presents a data assimilation procedure, the best linear unbiased estimator (BLUE), used with the goal of improving the peak discharge predictions generated by an event-based hydrological model Soil Conservation Service lag and route (SCS-LR). For a given prediction date, selected model inputs are corrected by assimilating discharge data observed at the basin outlet. This study is conducted on the Lez Mediterranean basin in southern France. The key objectives of this article are (i) to select the parameter(s) which allow for the most efficient and reliable correction of the simulated discharges, (ii) to demonstrate the impact of the correction of the initial condition upon simulated discharges, and (iii) to identify and understand conditions in which this technique fails to improve the forecast skill. The correction of the initial moisture deficit of the soil reservoir proves to be the most efficient control parameter for adjusting the peak discharge. Using data assimilation, this correction leads to an average of 12% improvement in the flood peak magnitude forecast in 75% of cases. The investigation of the other 25% of cases points out a number of precautions for the appropriate use of this data assimilation procedure.

scholarly journals Characteristics of rainfall events in regional climate model simulations for the Czech Republic

2017 ◽  
Vol 21 (2) ◽  
pp. 963-980 ◽  
Author(s):  
Vojtěch Svoboda ◽  
Martin Hanel ◽  
Petr Máca ◽  
Jan Kyselý
Keyword(s):  
Czech Republic ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Rainfall Event ◽  
Spatial Average ◽  
Total Precipitation ◽  
Rainfall Events ◽  
The Czech Republic ◽  
Simulated Event

Abstract. Characteristics of rainfall events in an ensemble of 23 regional climate model (RCM) simulations are evaluated against observed data in the Czech Republic for the period 1981–2000. Individual rainfall events are identified using the concept of minimum inter-event time (MIT) and only heavy events (15 % of events with the largest event depths) during the warm season (May–September) are considered. Inasmuch as an RCM grid box represents a spatial average, the effects of areal averaging of rainfall data on characteristics of events are investigated using the observed data. Rainfall events from the RCM simulations are then compared to those from the at-site and area-average observations. Simulated number of heavy events and seasonal total precipitation due to heavy events are on average represented relatively well despite the higher spatial variation compared to observations. RCM-simulated event depths are comparable to the area-average observations, while event durations are overestimated and other characteristics related to rainfall intensity are significantly underestimated. The differences between RCM-simulated and at-site observed rainfall event characteristics are in general dominated by the biases of the climate models rather than the areal-averaging effect. Most of the rainfall event characteristics in the majority of the RCM simulations show a similar altitude-dependence pattern as in the observed data. The number of heavy events and seasonal total precipitation due to heavy events increase with altitude, and this dependence is captured better by the RCM simulations with higher spatial resolution.

Impact of climate change on soil moisture condition in Nova Scotia

2012 ◽  
Author(s):  
Raheleh Malekian ◽  
Robert Gordon ◽  
Ali Madani ASABE Member ◽  
Seyyed Ebrahim Hashemi
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Nova Scotia ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Impact Of Climate Change

scholarly journals Diagnostic calibration of a hydrological model in an alpine area

2014 ◽  
Vol 11 (1) ◽  
pp. 1253-1300 ◽  
Author(s):  
Z. He ◽  
F. Tian ◽  
H. C. Hu ◽  
H. V. Gupta ◽  
H. P. Hu
Keyword(s):  
Hydrological Modeling ◽  
Hydrological Model ◽  
Generation Mechanism ◽  
Spatiotemporal Variability ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Runoff Generation ◽  
Alpine Area ◽  
Long Time ◽  
Tailan River Basin

Abstract. Hydrological modeling depends on single- or multiple-objective strategies for parameter calibration using long time sequences of observed streamflow. Here, we demonstrate a diagnostic approach to the calibration of a hydrological model of an alpine area in which we partition the hydrograph based on the dominant runoff generation mechanism (groundwater baseflow, glacier melt, snowmelt, and direct runoff). The partitioning reflects the spatiotemporal variability in snowpack, glaciers, and temperature. Model parameters are grouped by runoff generation mechanism, and each group is calibrated separately via a stepwise approach. This strategy helps to reduce the problem of equifinality and, hence, model uncertainty. We demonstrate the method for the Tailan River basin (1324 km2) in the Tianshan Mountains of China with the help of a semi-distributed hydrological model (THREW).

scholarly journals Effect of soil moisture condition on the conversion rate of oxamyl.

1979 ◽  
Vol 27 (3) ◽  
pp. 191-198
Author(s):  
J.H. Smelt ◽  
A. Dekker ◽  
M. Leistra
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Conversion Rate ◽  
Soil Moisture Content ◽  
Loamy Sand ◽  
Clay Loam ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Incubation Experiments ◽  
Wilting Point

The decomposition of oxamyl in four soils under moist conditions was measured in incubation experiments at 15 deg C. Half-lives of oxamyl in soils with moisture tensions of approx. -9.8 X 103 Pa were 13 days in a clay loam, 14 days in a loamy sand, 34 days in a peaty sand and 39 days in a humic loamy sand. The rate of oxamyl decomposition in the clay loam decreased with decreasing soil moisture content down to values for below wilting point. Oxamyl decomposition in the humic loamy sand decreased with decreasing soil moisture content, but increased sharply in the very dry range. (Abstract retrieved from CAB Abstracts by CABI’s permission)

scholarly journals Rainfall-Runoff Modeling Using NRCS-CN method and GIS approach

2020 ◽  
Author(s):  
Rekha Verma ◽  
Azhar Husain ◽  
Mohammed Sharif
Keyword(s):  
Hydrological Modeling ◽  
Curve Number ◽  
Geographical Information ◽  
Rainfall Runoff ◽  
Moisture Condition ◽  
Natural Resource Conservation ◽  
Antecedent Moisture ◽  
Natural Resource Conservation Service ◽  
Runoff Modeling ◽  
Runoff Depth

Rainfall-Runoff modeling is a hydrological modeling which is extremely important for water resources planning, development, and management. In this paper, Natural Resource Conservation Service-Curve Number (NRCS-CN) method along with Geographical Information System (GIS) approach was used to evaluate the runoff resulting from the rainfall of four stations, namely, Bilodra, Kathlal, Navavas and Rellawada of Sabarmati River basin. The rainfall data were taken for 10 years (2005-2014). The curve number which is the function of land use, soil and antecedent moisture condition (AMC) was generated in GIS platform. The CN value generated for AMC- I, II and III were 57.29, 75.39 and 87.77 respectively. Using NRCS-CN method, runoff depth was calculated for all the four stations. The runoff depth calculated with respect to the rainfall for Bilodra, Kathlal, Navavas and Rellawada shows a good correlation of 0.96. The computed runoff was compared with the observed runoff which depicted a good correlation of 0.73, 0.70, 0.76 and 0.65 for the four stations. This method results in speedy and precise estimation of runoff from a watershed.

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