scholarly journals Distributed model of hydrological and sediment transport processes in large river basins in Southeast Asia

2015 ◽  
Vol 12 (7) ◽  
pp. 6755-6797 ◽  
Author(s):  
S. Zuliziana ◽  
K. Tanuma ◽  
C. Yoshimura ◽  
O. C. Saavedra

Abstract. Soil erosion and sediment transport have been modeled at several spatial and temporal scales, yet few models have been reported for large river basins (e.g., drainage areas > 100 000 km2). In this study, we propose a process-based distributed model for assessment of sediment transport at a large basin scale. A distributed hydrological model was coupled with a process-based distributed sediment transport model describing soil erosion and sedimentary processes at hillslope units and channels. The model was tested on two large river basins: the Chao Phraya River Basin (drainage area: 160 000 km2) and the Mekong River Basin (795 000 km2). The simulation over 10 years showed good agreement with the observed suspended sediment load in both basins. The average Nash–Sutcliffe efficiency (NSE) and average correlation coefficient (r) between the simulated and observed suspended sediment loads were 0.62 and 0.61, respectively, in the Chao Phraya River Basin except the lowland section. In the Mekong River Basin, the overall average NSE and r were 0.60 and 0.78, respectively. Sensitivity analysis indicated that suspended sediment load is sensitive to detachability by raindrop (k) in the Chao Phraya River Basin and to soil detachability over land (Kf) in the Mekong River Basin. Overall, the results suggest that the present model can be used to understand and simulate erosion and sediment transport in large river basins.

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 56 ◽  
Author(s):  
Chelsea Dandridge ◽  
Bin Fang ◽  
Venkat Lakshmi

In large river basins where in situ data were limited or absent, satellite-based soil moisture estimates can be used to supplement ground measurements for land and water resource management solutions. Consistent soil moisture estimation can aid in monitoring droughts, forecasting floods, monitoring crop productivity, and assisting weather forecasting. Satellite-based soil moisture estimates are readily available at the global scale but are provided at spatial scales that are relatively coarse for many hydrological modeling and decision-making purposes. Soil moisture data are obtained from NASA’s soil moisture active passive (SMAP) mission radiometer as an interpolated product at 9 km gridded resolution. This study implements a soil moisture downscaling algorithm that was developed based on the relationship between daily temperature change and average soil moisture under varying vegetation conditions. It applies a look-up table using global land data assimilation system (GLDAS) soil moisture and surface temperature data, and advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and land surface temperature (LST). MODIS LST and NDVI are used to obtain downscaled soil moisture estimates. These estimates are then used to enhance the spatial resolution of soil moisture estimates from SMAP 9 km to 1 km. Soil moisture estimates at 1 km resolution are able to provide detailed information on the spatial distribution and pattern over the regions being analyzed. Higher resolution soil moisture data are needed for practical applications and modelling in large watersheds with limited in situ data, like in the Lower Mekong River Basin (LMB) in Southeast Asia. The 1 km soil moisture estimates can be applied directly to improve flood prediction and assessment as well as drought monitoring and agricultural productivity predictions for large river basins.


2018 ◽  
Author(s):  
Yongping Yuan ◽  
Ruoyu Wang ◽  
Ellen Cooter ◽  
Limei Ran ◽  
Prasad Daggupati ◽  
...  

Abstract. This study describes and implements an integrated, multimedia, process-based system-level approach to estimating nitrogen (N) fate and transport in large river basins. The modeling system includes the following components: 1) Community Multi-Scale Air Quality (CMAQ); 2) Water Research and Forecasting (WRF); 3) Environmental Policy Integrated Climate (EPIC); and 4) Soil and Water Assessment Tool (SWAT). The previously developed Fertilizer Emission Scenario Tool for the Community Multiscale Air Quality (FEST-C) system integrated EPIC with the WRF model and CMAQ. FEST-C, driven by process-based WRF weather simulations, includes atmospheric N additions to agricultural cropland, and agricultural cropland contributions to ammonia emissions. Watershed hydrology and water quality models need to be integrated with the system (FEST-C), however, so it can be used in large river basins to address impacts of fertilization, meteorology, and atmospheric N deposition on water quality. Objectives of this paper are to describe how to expand the previous effort by integrating a watershed model with the FEST-C (CMAQ/WRF/EPIC) modeling system, as well as demonstrate application of the Integrated Modeling System (IMS) to the Mississippi River Basin (MRB) to simulate streamflow and dissolved N loadings to the Gulf of Mexico (GOM). IMS simulation results generally agree with USGS observations/estimations; the annual simulated streamflow is 218.9 mm and USGS observation is 211.1 mm and the annual simulated dissolved N is 2.1 kg/ha. and the USGS estimation is 2.8 kg/ha. Integrating SWAT with the CMAQ/WRF/EPIC modeling system allows for its use within large river basins without losing EPIC’s more detailed biogeochemistry processes, which will strengthen assessment of impacts of future climate scenarios, regulatory and voluntary programs for nitrogen oxide air emissions, and land use and land management on N transport and transformation in large river basins.


Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 407
Author(s):  
Chenchen Ren ◽  
Guoyu Ren ◽  
Panfeng Zhang ◽  
Suonam Kealdrup Tysa ◽  
Yun Qin

The causes of the pan-evaporation decline have been debated, and few researches have been carried out on the possible effect of local land use and land cover change on the regional pan-observation data series. In this paper, the urbanization effect on the estimate of pan-evaporation trends over 1961–2017 was examined for the data series of 331 urban stations, applying a previously developed dataset of the reference stations, in seven large river basins of the China mainland. The trends of pan-evaporation difference series (transformed to anomaly percentage) between urban stations and reference stations were negative and statistically significant in all of the basins, indicating that urbanization significantly reduced the pan-evaporation. The urbanization-induced trend in the whole study region was −2.54%/decade for the urban stations. Except for the Yellow River Basin and the upper Yangtze River Basin, the urbanization effects in the other five large river basins of the country are all significant, with the mid and low reaches of the Yangtze River and the Songhua River registering the largest urbanization effects of −4.08%/decade and −4.06%/decade, respectively. Since the trends of regional average series for reference stations across half of the river basins are not statistically significant, the urbanization effect is a dominant factor for the observed decline in pan-evaporation. This finding would deepen our understanding of the regional and basin-wide change in pan-evaporation observed over the last decades.


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