Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density Conditions
Accurate soil moisture information is very important for real-time flood forecasting. Although satellite soil moisture observations are useful information, their validations are generally hindered by the large spatial difference with the point-based measurements, and hence they cannot be directly ap...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-01-01
|
| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2017/1086456 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832549520809918464 |
|---|---|
| author | Lu Zhuo Dawei Han |
| author_facet | Lu Zhuo Dawei Han |
| author_sort | Lu Zhuo |
| collection | DOAJ |
| description | Accurate soil moisture information is very important for real-time flood forecasting. Although satellite soil moisture observations are useful information, their validations are generally hindered by the large spatial difference with the point-based measurements, and hence they cannot be directly applied in hydrological modelling. This study adopts a widely applied operational hydrological model Xinanjiang (XAJ) as a hydrological validation tool. Two widely used microwave sensors (SMOS and AMSR-E) are evaluated, over two basins (French Broad and Pontiac) with different climate types and vegetation covers. The results demonstrate SMOS outperforms AMSR-E in the Pontiac basin (cropland), while both products perform poorly in the French Broad basin (forest). The MODIS NDVI thresholds of 0.81 and 0.64 (for cropland and forest basins, resp.) are very effective in dividing soil moisture datasets into “denser” and “thinner” vegetation periods. As a result, in the cropland, the statistical performance is further improved for both satellites (i.e., improved to NSE = 0.74, RMSE = 0.0059 m and NSE = 0.58, RMSE = 0.0066 m for SMOS and AMER-E, resp.). The overall assessment suggests that SMOS is of reasonable quality in estimating basin-scale soil moisture at moderate-vegetated areas, and NDVI is a useful indicator for further improving the performance. |
| format | Article |
| id | doaj-art-6edb2a99a063458186624b2cc1b188c8 |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-6edb2a99a063458186624b2cc1b188c82025-02-03T06:11:10ZengWileyAdvances in Meteorology1687-93091687-93172017-01-01201710.1155/2017/10864561086456Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density ConditionsLu Zhuo0Dawei Han1WEMRC, Department of Civil Engineering, University of Bristol, Bristol, UKWEMRC, Department of Civil Engineering, University of Bristol, Bristol, UKAccurate soil moisture information is very important for real-time flood forecasting. Although satellite soil moisture observations are useful information, their validations are generally hindered by the large spatial difference with the point-based measurements, and hence they cannot be directly applied in hydrological modelling. This study adopts a widely applied operational hydrological model Xinanjiang (XAJ) as a hydrological validation tool. Two widely used microwave sensors (SMOS and AMSR-E) are evaluated, over two basins (French Broad and Pontiac) with different climate types and vegetation covers. The results demonstrate SMOS outperforms AMSR-E in the Pontiac basin (cropland), while both products perform poorly in the French Broad basin (forest). The MODIS NDVI thresholds of 0.81 and 0.64 (for cropland and forest basins, resp.) are very effective in dividing soil moisture datasets into “denser” and “thinner” vegetation periods. As a result, in the cropland, the statistical performance is further improved for both satellites (i.e., improved to NSE = 0.74, RMSE = 0.0059 m and NSE = 0.58, RMSE = 0.0066 m for SMOS and AMER-E, resp.). The overall assessment suggests that SMOS is of reasonable quality in estimating basin-scale soil moisture at moderate-vegetated areas, and NDVI is a useful indicator for further improving the performance.http://dx.doi.org/10.1155/2017/1086456 |
| spellingShingle | Lu Zhuo Dawei Han Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density Conditions Advances in Meteorology |
| title | Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density Conditions |
| title_full | Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density Conditions |
| title_fullStr | Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density Conditions |
| title_full_unstemmed | Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density Conditions |
| title_short | Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density Conditions |
| title_sort | hydrological evaluation of satellite soil moisture data in two basins of different climate and vegetation density conditions |
| url | http://dx.doi.org/10.1155/2017/1086456 |
| work_keys_str_mv | AT luzhuo hydrologicalevaluationofsatellitesoilmoisturedataintwobasinsofdifferentclimateandvegetationdensityconditions AT daweihan hydrologicalevaluationofsatellitesoilmoisturedataintwobasinsofdifferentclimateandvegetationdensityconditions |