Long-term hydrologic simulation using SCS-CN-based improved soil moisture accounting procedure

2010 ◽  
Vol 25 (4) ◽  
pp. 561-579 ◽  
Author(s):  
Dilip G. Durbude ◽  
Manoj K. Jain ◽  
Surendra K. Mishra
2015 ◽  
Vol 51 (1) ◽  
pp. 506-523 ◽  
Author(s):  
Simon A. Mathias ◽  
Todd H. Skaggs ◽  
Simon A. Quinn ◽  
Sorcha N. C. Egan ◽  
Lucy E. Finch ◽  
...  

2007 ◽  
Vol 21 (21) ◽  
pp. 2872-2881 ◽  
Author(s):  
R. K. Sahu ◽  
S. K. Mishra ◽  
T. I. Eldho ◽  
M. K. Jain

RBRH ◽  
2020 ◽  
Vol 25 ◽  
Author(s):  
Bibiana Rodrigues Colossi ◽  
Carlos Eduardo Morelli Tucci

ABSTRACT Long-term soil moisture forecasting allows for better planning in sectors as agriculture. However, there are still few studies dedicated to estimate soil moisture for long lead times, which reflects the difficulties associated with this topic. An approach that could help improving these forecasts performance is to use ensemble predictions. In this study, a soil moisture forecast for lead times of one, three and six months in the Ijuí River Basin (Brazil) was developed using ensemble precipitation forecasts and hydrologic simulation. All ensemble members from three climatologic models were used to run the MGB hydrological model, generating 207 soil moisture forecasts, organized in groups: (A) for each model, the most frequent soil moisture interval predicted among the forecasts made with each ensemble member, (B) using each model’s mean precipitation, (C) considering a super-ensemble, and (D) the mean soil moisture interval predicted among group B forecasts. The results show that long-term soil moisture based on precipitation forecasts can be useful for identifying periods drier or wetter than the average for the studied region. Nevertheless, estimation of exact soil moisture values remains limited. Forecasts groups B and D performed similarly to groups A and C, and require less data management and computing time.


2020 ◽  
Author(s):  
Zhenlei Yang ◽  
Wolfgang Kurtz ◽  
Sebastian Gebler ◽  
Lennart Schüler ◽  
Stefan Kollet ◽  
...  

<p>Integrated terrestrial systems modeling is important for the comprehensive investigation of the coupled terrestrial water, energy and biogeochemical cycles. In this work, we applied the Terrestrial Systems Modeling Platform (TSMP) to the two meso-scale catchments in Germany (Rur and Bode) to conduct a long time hydrologic simulation with a focus on variables such as soil moisture, evapotranspiration (ET) and groundwater recharge. Simulations for the Rur and Bode catchments were performed at three different spatial horizontal model resolutions (1000, 500, and 200m) with CLM and CLM-PF in TSMP. Each of the three resolution models was run for 24 years (1995-2018) with transient atmospheric forcings derived from COSMO-REA6 data. The long term simulation results show that the summer of 2018 resulted in the lowest soil moisture content over the time series that is around 0.20, lower than the dry summers of 1995 and 2003. ET was more reduced in July-August 2018 due to the decrease of soil moisture content during this period. Nevertheless, actual evapotranspiration was even in the summer of 2018 often not limited by soil moisture content. For these catchments ET is most of the time energy limited. In addition, the vegetation evaporation (resulting from interception) accounts for the smallest percentage of the ET (ca. 20%), whereas the vegetation transpiration and soil evaporation account for almost the same percentage of the total ET (each 40% approximately). Both the CLM and CLM-PF simulation results indicate that grid coarsening (lower model resolution) leads to larger ET and soil moisture content, which is related to the decreasing slope gradient with grid coarsening. The analysis of groundwater recharge is underway.</p>


Author(s):  
Erika Lira da Silva ◽  
Allan Sarmento Vieira

Objetivou-se realizar uma simulação integrada nos reservatórios Engenheiro Ávidos e São Gonçalo, localizados, na Sub-bacia do Alto Piranhas no Estado da Paraíba, utilizando o modelo de rede de fluxo Acquanet. Utilizou-se o modelo tipo transformação chuva-vazão SMAP (Soil Moisture Accounting Procedure) para complementar a série de vazões naturais no período de 2010 a 2016. Assim a simulação realizada considerou uma série histórica de 1962 a 2016, com um cenário futuro onde foram adotados valores das demandas projetadas para o ano de 2032. Analisando a parte operacional dos reservatórios foi observado, no período simulado, que os mesmos atingiram seu volume máximo em muitos meses; na maioria dos períodos o volume meta foi respeitado; o volume mínimo foi atingido em alguns momentos devido aos baixos índices pluviométricos, fato que se intensificou nos últimos anos. Quanto às demandas, o abastecimento humano e dessedentação apresentaram confiabilidade acima dos 90%, já para a irrigação e indústria, o número de falhas foi maior. No cenário futuro, os resultados tiveram uma representação diferente, em poucos momentos chegaram ao volume máximo, por muitos meses operaram no volume mínimo, não conseguindo atender ao requerimento operacional do volume meta, e consequentemente o atendimento às demandas também não foi satisfatório. As falhas ocorreram no abastecimento humano e animal nos dois reservatórios, onde a confiabilidade ficou acima de 70%, e as demandas irrigação e indústria apresentaram um grande déficit de atendimento.


2017 ◽  
Vol 18 (1) ◽  
pp. 151-158 ◽  
Author(s):  
Angela L. Bowman ◽  
Kristie J. Franz ◽  
Terri S. Hogue

Abstract A satellite-based potential evapotranspiration (PET) estimate derived from Moderate Resolution Imaging Spectroradiometer (MODIS) observations was tested for input to the spatially lumped and gridded Sacramento Soil Moisture Accounting (SAC-SMA) model. The 15 forecast points within the National Weather Service (NWS) North Central River Forecast Center (NCRFC) forecasting region were the basis for this analysis. Through a series of case studies, the MODIS-derived PET estimate (M-PET) was evaluated for input to the SAC-SMA model by comparing streamflow simulations with those from traditional SAC-SMA evapotranspiration (ET) demand. Two prior studies have evaluated the M-PET data 1) to compute new long-term average ET demand values and 2) to input a time series (i.e., daily time-varying PET) to the NWS Hydrology Laboratory–Research Distributed Hydrologic Model (HL-RDHM), a spatially distributed version of the SAC-SMA model. This current paper presents results from a third test in which the M-PET time series is input to the lumped SAC-SMA model. In all cases, evaluation is between the M-PET data and the long-term average values used by the NWS. Similar to prior studies, results of the current analysis are mixed with improved model evaluation statistics for 4 of 15 basins tested. Of the three cases, using the time-varying M-PET as input to the distributed SAC-SMA model led to the most promising results, with model simulations that are at least as good as those when using the SAC-SMA ET demand. Analyses of the model-simulated ET suggest that the time-varying M-PET input may produce a more physically realistic representation of ET processes in both the lumped and distributed versions of the SAC-SMA model.


Sign in / Sign up

Export Citation Format

Share Document