scholarly journals A Prior Estimation of the Spatial Distribution Parameter of Soil Moisture Storage Capacity Using Satellite-Based Root-Zone Soil Moisture Data

2019 ◽  
Vol 11 (21) ◽  
pp. 2580 ◽  
Author(s):  
Yifei Tian ◽  
Lihua Xiong ◽  
Bin Xiong ◽  
Ruodan Zhuang
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Storage Capacity ◽  
Spatial Information ◽  
Root Zone ◽  
River Catchment ◽  
Soil Moisture Storage ◽  
Soil Moisture Data ◽  
Moisture Storage ◽  
The Impact

Integration of satellite-based data with hydrological modelling was generally conducted via data assimilation or model calibration, and both approaches can enhance streamflow predictions. In this study, we assessed the feasibility of another approach that uses satellite-based soil moisture data to directly estimate the parameter β to represent the degree of the spatial distribution of soil moisture storage capacity in the semi-distributed Hymod model. The impact of using historical root-zone soil moisture data from the Soil Moisture Active Passive (SMAP) mission on the prior estimation of the parameter β was explored. Two different ways to incorporate the root-zone soil moisture data to estimate the parameter β are proposed, i.e., one is to derive a priori distribution of β , and the other is to derive a fixed value for β . The simulations of the Hymod models employing the two ways to estimate β are compared with the results produced by the original model, i.e., the one without employing satellite-based data to estimate the parameter β , at three study catchments (the Upper Hanjiang River catchment, the Xiangjiang River catchment, and the Ganjiang River catchment). The results illustrate that the two ways to incorporate the SMAP root-zone soil moisture data in order to predetermine the parameter β of the semi-distributed Hymod model both perform well in simulating streamflow during the calibration period, and a slight improvement was found during the validation period. Notably, deriving a fixed β value from satellite soil moisture data can provide better performance for ungauged catchments despite reducing the model freedom degrees due to fixing the β value. It is concluded that the robustness of the Hymod model in predicting the streamflow can be improved when the spatial information of satellite-based soil moisture data is utilized to estimate the parameter β .

Flood forecasting that considers the impact of hydraulic projects by an improved TOPMODEL model in the Wudaogou basin, Northeast China

2016 ◽  
Vol 16 (5) ◽  
pp. 1467-1476 ◽  
Author(s):  
Yong Peng ◽  
Jinggang Chu ◽  
Xinguo Sun ◽  
Huicheng Zhou ◽  
Xiaoli Zhang
Keyword(s):  
Water Conservation ◽  
Northeast China ◽  
Storage Capacity ◽  
Flood Simulation ◽  
Soil Moisture Storage ◽  
Moisture Storage ◽  
Flood Simulations ◽  
Model Parameter Uncertainty ◽  
The Impact ◽  
Engineering Projects

Many hydraulic projects such as reservoirs, ponds and paddy fields as well as soil and water conservation engineering projects have been constructed to improve utilization of water resources upstream of the Wudaogou station basin in Northeast China in recent years. As a result, the local hydrological characteristics of the basin and the flood runoff and process have been changed. These changes in the basin characteristics make basin hydrological forecasting more difficult. In order to model and assess this situation, the TOPMODEL, which includes the dynamic soil moisture storage capacity (DSMSC-TOPMODEL), is used in this study to simulate the flood impact of hydraulic projects. Furthermore, the Bayesian method is used to evaluate model parameter uncertainty and assess the TOPMODEL's performance over the basin. Flood simulation results show that accuracy is significantly improved when the stock version of TOPMODEL is replaced with DSMSC-TOPMODEL, with the qualified ratio of forecasting runoff yield increasing from 65% in the former to 88% in the latter. Moreover, these flood simulations are more suitable for helping observers visualize the process.

scholarly journals Streamflow data assimilation for soil moisture analysis

2010 ◽  
Vol 3 (1) ◽  
pp. 1-12 ◽  
Author(s):  
K. Warrach-Sagi ◽  
V. Wulfmeyer
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Land Surface ◽  
Climate Models ◽  
Root Zone ◽  
Weather Forecast ◽  
Surface Model ◽  
River Catchment ◽  
Streamflow Data ◽  
The Impact

Abstract. Streamflow depends on the soil moisture of a river catchment and can be measured with relatively high accuracy. The soil moisture in the root zone influences the latent heat flux and, hence, the quantity and spatial distribution of atmospheric water vapour and precipitation. As numerical weather forecast and climate models require a proper soil moisture initialization for their land surface models, we enhanced an Ensemble Kalman Filter to assimilate streamflow time series into the multi-layer land surface model TERRA-ML of the regional weather forecast model COSMO. The impact of streamflow assimilation was studied by an observing system simulation experiment in the Enz River catchment (located at the downwind side of the northern Black Forest in Germany). The results demonstrate a clear improvement of the soil moisture field in the catchment. We illustrate the potential of streamflow data assimilation for weather forecasting and discuss its spatial and temporal requirements for a corresponding, automated river gauging network.

scholarly journals Assessing the Increase in Soil Moisture Storage Capacity and Nutrient Enhancement of Different Organic Amendments in Paddy Soil

Agriculture ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 44
Author(s):  
Ahmad Numery Ashfaqul Haque ◽  
Md. Kamal Uddin ◽  
Muhammad Firdaus Sulaiman ◽  
Adibah Mohd Amin ◽  
Mahmud Hossain ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Rice Husk ◽  
Oil Palm ◽  
Paddy Soil ◽  
Storage Capacity ◽  
Organic Amendments ◽  
Chemical Properties ◽  
Total Carbon ◽  
Soil Moisture Storage ◽  
Moisture Storage

Increasing soil moisture storage capacity is a strategy that can be implemented to minimize the use of water in paddy rice cultivation. Organic materials from different sources have the potential to increase soil moisture storage and nutrient enrichment. An incubation study was conducted to evaluate the incorporation of five selected organic amendments—as follows: rice husk biochar (RHB), oil palm empty fruit bunch biochar (EFBB), compost (COMP), rice husk ash (RHA), and oil palm bunch ash (PBA), with a control (no amendment) on soil moisture storage and some chemical properties of soil. The soil was incubated with five amendments for 60 days and sampled at 15-day intervals. After completion of the incubation, a greater extent of gravimetric water content was observed from RHB (0.46 g g−1) and EFBB (0.45 g g−1) followed by compost (0.40 g g−1). The addition of organic amendments significantly influenced soil chemical properties. Maximum soil pH was altered by PBA followed by EFBB compared to its initial value (5.01). The inclusion of EFBB finally contributed to the highest amount of total carbon (7.82%) and nitrogen (0.44%). The addition of PBA showed the highest available P and exchangeable K followed by RHB when compared with the amendments. The results indicated that RHB, EFBB, and compost retain more soil moisture compared to ash sources and added soil nutrients, indicating their potential to improve the chemical and hydrological properties of paddy soil.

scholarly journals Influence of Various Soil and Water Conservation Methods on the Moisture Balance at Coffee Plant Root Zone

2022 ◽  
Author(s):  
Lina Saraswati ◽  
Sugeng Prijono ◽  
Budi Prasetya
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Water Conservation ◽  
Root Zone ◽  
Dry Season ◽  
Soil And Water Conservation ◽  
Soil Moisture Storage ◽  
Moisture Balance ◽  
Moisture Storage ◽  
Soil And Water

Background: The study of the moisture balance can be used to suppose the plants water requirement and the plants water use efficiency. The moisture balance influenced by climate factor, therefore climate change can affect the moisture balance especially in rainfed. Therefore, an effort is needed to manage soil moisture in rainfed as a climate change mitigation measure: soil and water conservation. This study aimed to determine the influence of soil and water conservation on the moisture balance in the coffee root zone. Methods: This study was conducted at people’s coffee plantation of Argotirto village, Sumbermanjing Wetan District, Malang Regency, located between 8.2411-8.1443 S and 112.4031-112.4634 E. Observation were made on February to November 2020, divided into observations in the wet season, dry seasons and flowering period. The observation plots consisted of terraced plot (P0), terraced + straight silt pit (P1), terraced + L-shaped silt pit (P2) and terrace + biopore (P3). The observation variables were: soil physical characteristics and moisture balance components there were precipitation, percolation, runoff, evapotranspiration and soil moisture storage. Result: At P1, the runoff depth was 80.89% lower and the percolation was 44.22% higher than P0. The total soil moisture storage at P1 was 20.06% higher than P0 in the dry season, indicating that P1 could increase the period of surplus moisture in the dry season.

scholarly journals The impact of land use/land cover changes and hydraulic structures on flood recession process

2017 ◽  
Vol 8 (3) ◽  
pp. 375-387 ◽  
Author(s):  
Chun Chang ◽  
Ping Feng
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Land Cover ◽  
Storage Capacity ◽  
Hydraulic Structures ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Soil Moisture Storage ◽  
Recession Curves ◽  
Moisture Storage

Intensified human activities have brought about great changes in runoff generation and convergence. As a significant part of the hydrological process, recession flows represent the capacity of a river basin to store rain and drain it during dry periods; therefore study of the influence of human-induced factors on flood flow recession is of great importance. The Fuping sub-catchment was selected as the study area. Comparisons of land use/land cover and soil moisture storage capacity changes were made between reference and impaired periods. In addition, 64 recession flows during 1958–2005 were simulated using the linear and non-linear reservoir recession models. Then the influence of land use/land cover changes and hydraulic structures on recession flows was identified. Results showed that grassland and cultivated land declined in area while forests increased. At the same time, there was a sharp increase in the soil moisture storage capacity. The non-linear recession model, being more accurate than the linear recession model, was used to simulate the recession process. Compared with recession curves before 1980, the initial outflow from the basin declined while the power law coefficient and recession duration increased; the power law exponent was relatively constant. Furthermore, the shapes of recession curves were flattened.

scholarly journals The Normalized Difference Infrared Index (NDII) as a proxy for soil moisture storage in hydrological modelling

2015 ◽  
Vol 12 (8) ◽  
pp. 8419-8457 ◽  
Author(s):  
N. Sriwongsitanon ◽  
H. Gao ◽  
H. H. G. Savenije ◽  
E. Maekan ◽  
S. Saengsawang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Root Zone ◽  
Hydrological Modelling ◽  
Dry Season ◽  
Leaf Water ◽  
Wet Season ◽  
Exponential Relationship ◽  
Temporal And Spatial Distribution ◽  
Soil Moisture Storage ◽  
Moisture Storage

Abstract. With remote sensing we can readily observe the Earth's surface, but looking under the surface into the root zone of vegetation is still a major challenge. Yet knowledge on the dynamics of soil moisture in the root zone is essential for agriculture, land–atmosphere interaction and hydrological modelling, alike. In this paper we develop a novel approach to monitor the soil moisture storage deficit in the root zone of vegetation, by using the remotely sensed Normalised Difference Infrared Index (NDII) in the Upper Ping River Basin (UPRB) in northern Thailand. Satellite data from the Moderate Resolution Imaging Spectro-radiometer (MODIS) was used to evaluate the NDII over an 8 day period, covering the study area from 2001 to 2013. The results show that NDII values decrease sharply at the end of the wet season in October and reach lowest values near the end of the dry season in March. The values then increase abruptly after rains have started, but vary in an insignificant manner from the middle to the late rainy season. The NDII proves to be a very strong proxy for moisture storage deficit in the root zone, which is a crucial component of hydrological models. In addition, the NDII appears to be a reliable indicator for the temporal and spatial distribution of drought conditions in the UPRB. The 8 day average NDII values were found to correlate very well with the 8 day average soil moisture content (SU) simulated by FLEXL (rainfall–runoff model) at 8 runoff stations during the dry season – giving an average R2 value 0.87 on an exponential relationship, while for the wet season it reduced to be around 0.61. Apparently, the NDII is an effective index for the moisture storage in the root zone during the time of moisture deficit, and a powerful indicator to assess droughts. In the dry season, when plants are exposed to water stress, the leaf-water deficit increases steadily. Once leaf-water is close to saturation – mostly at the end of the wet season – leaf characteristics and NDII values do not vary significantly, causing lower correlation between NDII and Su in the wet season. However, the correlations between NDII and Su still remain high for both seasons and therefore the product can be used to define drought situations throughout the year and be of use to water management.

scholarly journals Streamflow data assimilation for soil moisture analysis

2009 ◽  
Vol 2 (1) ◽  
pp. 551-579 ◽  
Author(s):  
K. Warrach-Sagi ◽  
V. Wulfmeyer
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Land Surface ◽  
Climate Models ◽  
Root Zone ◽  
Weather Forecast ◽  
Surface Model ◽  
River Catchment ◽  
Streamflow Data ◽  
The Impact

Abstract. Streamflow depends on the soil moisture of a river catchment and can be measured with relatively high accuracy. The soil moisture in the root zone influences the latent heat flux and hence the quantity and spatial distribution of atmospheric water vapour and precipitation. As numerical weather forecast and climate models require a proper soil moisture initialization for their land surface models, we enhanced an Ensemble Kalman Filter to assimilate streamflow timeseries into the multi-layer land surface model TERRA-ML of the regional weather forecast model COSMO. The impact of streamflow assimilation was studied by an observing system simulation experiment in the Enz River catchment (located at the downwind side of the northern Black Forest in Germany). The results demonstrate a clear improvement of the soil moisture field in the catchment. We illustrate the potential of streamflow data assimilation for weather forecasting and discuss its spatial and temporal requirements for a corresponding, automated river gauging network.

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