Application of GSMaP on estimating rainfall condition in Jakarta during 16 December 2019-14 January 2020

2021 ◽  
Author(s):  
Amalia Nurlatifah ◽  
Indah Susanti ◽  
Sinta Berliana Sipayung ◽  
Hidayatul Latifah
Keyword(s):  
Author(s):  
Juan An ◽  
Jibiao Geng ◽  
Huiling Yang ◽  
Hongli Song ◽  
Bin Wang

Seepage plays a key role in nutrient loss and easily occurs in widely-used contour ridge systems due to the ponding process. However, the characteristics of nutrient loss and its influential factors under seepage with rainfall condition in contour ridge systems are still unclear. In this study, 23 seepage and rainfall simulation experiments are arranged in an orthogonal rotatable central composite design to investigate the role of ridge height, row grade, and field slope on Nitrate (NO3−–N) and Orthophosphate (PO4+3–P) losses resulting from seepage in contour ridge systems. In total, three types of NO3−–N and PO4+3–P loss were observed according to erosion processes of inter-rill–headward, inter-rill–headward–contour failure, and inter-rill–headward–contour failure–rill. Our results demonstrated that second-order polynomial regression models were obtained to predict NO3−–N and PO4+3–P loss with the independent variables of ridge height, row grade, and field slope. Ridge height was the most important factor for nutrient loss, with a significantly positive effect and the greatest contribution (52.35–53.47%). The secondary factor of row grade exerted a significant and negative effect, and was with a contribution of 19.86–24.11% to nutrient loss. The interaction between ridge height and row grade revealed a significantly negative effect on NO3−–N loss, whereas interactions among the three factors did not significantly affect PO4+3–P loss. Field slope only significantly affected NO3−–N loss. The optimal design of a contour ridge system to control nutrient loss was obtained at ridge height of 8 cm, row grade of 2°, and field slope of 6.5°. This study provides a method to assess and model nutrient loss, and improves guidance to implement contour ridge systems in terms of nutrient loss control.


2014 ◽  
Vol 501-504 ◽  
pp. 8-11
Author(s):  
Jing Sheng Bian ◽  
Chao Sheng Bian ◽  
Zhi Ming Zhu

Rainfall is one of the most important factors of the slope stability. After the "5.12" earthquake, there are a large number of loose solid produced by earthquake on the mountain, which leads to the soils strength loss in the earthquake disaster zones. and induces landslides and collapses easily in the heavy rainfall condition. The soil parameters obtained from the tests, the scene investigation of the Erman mountain landslide of Han Yuan County, the new developed control of ArcGIS to obtain intuitive landslide warning graphs have been carried out. Results show that the picture of hazard grade is consistent with the actual situation of landslide on Erman mountain. It will provide a scientific way to analyze the influence of heavy rainfall on slope stability.


2019 ◽  
Vol 1 (11) ◽  
Author(s):  
Ichirow Kaihotsu ◽  
Jun Asanuma ◽  
Kentaro Aida ◽  
Dambaravjaa Oyunbaatar

Abstract This study evaluated the Advanced Microwave Scanning Radiometer 2 (AMSR2) L2 soil moisture product (ver. 3) using in situ hydrological observational data, acquired over 7 years (2012–2018), from a 50 × 50 km flat area of the Mongolian Plateau covered with bare soil, pasture and shrubs. Although AMSR2 slightly underestimated soil moisture content at 3-cm depth, satisfactory timing was observed in both the response patterns and the in situ soil moisture data, and the differences between these factors were not large. In terms of the relationship between AMSR2 soil moisture from descending orbits and in situ measured soil moisture at 3-cm depth, the values of the RMSE (m3/m3) and the bias (m3/m3) varied from 0.028 to 0.063 and from 0.011 to − 0.001 m3/m3, respectively. The values of the RMSE and bias depended on rainfall condition. The mean value of the RMSE for the 7-year period was 0.042 m3/m3, i.e., lower than the target accuracy 0.050 m3/m3. The validation results for descending orbits were found slightly better than for ascending orbits. Comparison of the Soil Moisture and Ocean Salinity (SMOS) soil moisture product with the AMSR2 L2 soil moisture product showed that AMSR2 could observe surface soil moisture with nearly same accuracy and stability. However, the bias of the AMSR2 soil moisture measurement was slightly negative and poorer than that of SMOS with deeper soil moisture measurement. It means that AMSR2 cannot effectively measure soil moisture at 3-cm depth. In situ soil temperature at 3-cm depth and surface vegetation (normalized difference vegetation index) did not influence the underestimation of AMSR2 soil moisture measurements. These results suggest that a possible cause of the underestimation of AMSR2 soil moisture measurements is the difference between the depth of the AMSR2 observations and in situ soil moisture measurements. Overall, this study proved the AMSR2 L2 soil moisture product has been useful for monitoring daily surface soil moisture over large grassland areas and it clearly demonstrated the high-performance capability of AMSR2 since 2012.


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