scholarly journals Downscaling of SMAP Soil Moisture in the Lower Mekong River Basin

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 56 ◽  
Author(s):  
Chelsea Dandridge ◽  
Bin Fang ◽  
Venkat Lakshmi
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
River Basin ◽  
River Basins ◽  
Large River ◽  
Mekong River ◽  
Mekong River Basin ◽  
In Situ Data ◽  
Large River Basins

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.

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
Keyword(s):  
Sediment Transport ◽  
Suspended Sediment ◽  
River Basin ◽  
River Basins ◽  
Large River ◽  
Mekong River ◽  
Distributed Model ◽  
Mekong River Basin ◽  
Chao Phraya River ◽  
Large River Basins

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.

scholarly journals Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia)

2019 ◽  
Vol 11 (22) ◽  
pp. 2709 ◽  
Author(s):  
Chelsea Dandridge ◽  
Venkat Lakshmi ◽  
John Bolten ◽  
Raghavan Srinivasan
Keyword(s):  
Southeast Asia ◽  
River Basin ◽  
Watershed Modeling ◽  
Rain Gauge ◽  
Mekong River ◽  
Coefficient Of Determination ◽  
Mekong River Basin ◽  
In Situ Data ◽  
Rainfall Estimates

Satellite-based precipitation is an essential tool for regional water resource applications that requires frequent observations of meteorological forcing, particularly in areas that have sparse rain gauge networks. To fully realize the utility of remotely sensed precipitation products in watershed modeling and decision-making, a thorough evaluation of the accuracy of satellite-based rainfall and regional gauge network estimates is needed. In this study, Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42 v.7 and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) daily rainfall estimates were compared with daily rain gauge observations from 2000 to 2014 in the Lower Mekong River Basin (LMRB) in Southeast Asia. Monthly, seasonal, and annual comparisons were performed, which included the calculations of correlation coefficient, coefficient of determination, bias, root mean square error (RMSE), and mean absolute error (MAE). Our validation test showed TMPA to correctly detect precipitation or no-precipitation 64.9% of all days and CHIRPS 66.8% of all days, compared to daily in-situ rainfall measurements. The accuracy of the satellite-based products varied greatly between the wet and dry seasons. Both TMPA and CHIRPS showed higher correlation with in-situ data during the wet season (June–September) as compared to the dry season (November–January). Additionally, both performed better on a monthly than an annual time-scale when compared to in-situ data. The satellite-based products showed wet biases during months that received higher cumulative precipitation. Based on a spatial correlation analysis, the average r-value of CHIRPS was much higher than TMPA across the basin. CHIRPS correlated better than TMPA at lower elevations and for monthly rainfall accumulation less than 500 mm. While both satellite-based products performed well, as compared to rain gauge measurements, the present research shows that CHIRPS might be better at representing precipitation over the LMRB than TMPA.

scholarly journals Integrating Multi-Media Models to Assess Nitrogen Losses from the Mississippi River Basin to the Gulf of Mexico

2018 ◽  
Author(s):  
Yongping Yuan ◽  
Ruoyu Wang ◽  
Ellen Cooter ◽  
Limei Ran ◽  
Prasad Daggupati ◽  
...  
Keyword(s):  
Water Quality ◽  
Air Quality ◽  
Gulf Of Mexico ◽  
River Basin ◽  
Mississippi River ◽  
River Basins ◽  
Large River ◽  
System Level ◽  
Mississippi River Basin ◽  
Large River Basins

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.

scholarly journals Upstream GPS Vertical Displacement and its Standardization for Mekong River Basin Surface Runoff Reconstruction and Estimation

2019 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Hok Sum Fok ◽  
Linghao Zhou ◽  
Yongxin Liu ◽  
Zhongtian Ma ◽  
Yutong Chen
Keyword(s):  
Time Series ◽  
River Water ◽  
River Basin ◽  
Relative Error ◽  
Surface Runoff ◽  
Water Discharge ◽  
Vertical Displacement ◽  
Mekong River ◽  
Mekong River Basin

Surface runoff (R), which is another expression for river water discharge of a river basin, is a critical measurement for regional water cycles. Over the past two decades, river water discharge has been widely investigated, which is based on remotely sensed hydraulic and hydrological variables as well as indices. This study aims to demonstrate the potential of upstream global positioning system (GPS) vertical displacement (VD) and its standardization to statistically derive R time series, which has not been reported in recent literature. The correlation between the in situ R at estuaries and averaged GPS-VD and its standardization in the river basin upstream on a monthly temporal scale of the Mekong River Basin (MRB) is examined. It was found that the reconstructed R time series from the latter agrees with and yields a similar performance to that from the terrestrial water storage based on gravimetric satellite (i.e., Gravity Recovery and Climate Experiment (GRACE)) and traditional remote sensing data. The reconstructed R time series from the standardized GPS-VD was found to have a 2–7% accuracy increase against those without standardization. On the other hand, it is comparable to data that are obtained by the Palmer drought severity index (PDSI). Similar accuracies are exhibited by the estimated R when externally validated through another station location with in situ time series. The comparison of the estimated R at the entrance of river delta against that at the estuaries indicates a 1–3% relative error induced by the residual ocean tidal effect at the estuary. The reconstructed R from the standardized GPS-VD yields the lowest total relative error of less than 9% when accounting for the main upstream area of the MRB. The remaining errors may be the result of the combined effect of the proposed methodology, remaining environmental signals in the data time series, and potential time lag (less than a month) between the upstream MRB and estuary.

scholarly journals Urbanization Significantly Affects Pan-Evaporation Trends in Large River Basins of China Mainland

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 407
Author(s):  
Chenchen Ren ◽  
Guoyu Ren ◽  
Panfeng Zhang ◽  
Suonam Kealdrup Tysa ◽  
Yun Qin
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
River Basins ◽  
Large River ◽  
Dominant Factor ◽  
Data Series ◽  
Pan Evaporation ◽  
Urbanization Effect ◽  
China Mainland ◽  
Large River Basins

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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