Your search found 6 records
1 Brocca, L.; Crow, W. T.; Ciabatta, L.; Massari, C.; de Rosnay, P.; Enenkel, M.; Hahn, S.; Amarnath, Giriraj; Camici, S.; Tarpanelli, A.; Wagner, W. 2017. A review of the applications of ASCAT [Advanced SCATterometer] soil moisture products. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(5):2285-2306. [doi: https://doi.org/10.1109/JSTARS.2017.2651140]
Soil moisture ; Hydrology ; Remote sensing ; Weather forecasting ; Radar ; Meteorological observations ; Satellite observation ; Hydrological cycle ; Climate change ; Rain ; Flooding ; Precipitation ; Evaporation ; Evapotranspiration ; Landslides
(Location: IWMI HQ Call no: e-copy only Record No: H048009)
Remote sensing of soil moisture has reached a level of good maturity and accuracy for which the retrieved products are ready to use in real-world applications. Due to the importance of soil moisture in the partitioning of the water and energy fluxes between the land surface and the atmosphere, a wide range of applications can benefit from the availability of satellite soil moisture products. Specifically, the Advanced SCATterometer (ASCAT) on board the series of Meteorological Operational (Metop) satellites is providing a near real time (and long-term, 9+ years starting from January 2007) soil moisture product, with a nearly daily (sub-daily after the launch of Metop-B) revisit time and a spatial sampling of 12.5 and 25 km. This study first performs a review of the climatic, meteorological, and hydrological studies that use satellite soil moisture products for a better understanding of the water and energy cycle. Specifically, applications that consider satellite soil moisture product for improving their predictions are analyzed and discussed. Moreover, four real examples are shown in which ASCAT soil moisture observations have been successfully applied toward: 1) numerical weather prediction, 2) rainfall estimation, 3) flood forecasting, and 4) drought monitoring and prediction. Finally, the strengths and limitations of ASCAT soil moisture products and the way forward for fully exploiting these data in real-world applications are discussed.
2 Mustafa, S. M. T.; Vanuytrecht, E.; Huysmans, M. 2017. Combined deficit irrigation and soil fertility management on different soil textures to improve wheat yield in drought-prone Bangladesh. Agricultural Water Management, 191:124-137. [doi: https://doi.org/10.1016/j.agwat.2017.06.011]
Irrigation management ; Water deficit ; Soil fertility ; Soil management ; Soil texture ; Water productivity ; Models ; Crop yield ; Wheat ; Irrigation scheduling ; Soil water content ; Soil types ; Meteorological observations ; Drought ; Precipitation ; Strategies / Bangladesh / Dhaka / Mymensigh / Rajshahi / Rangpur
(Location: IWMI HQ Call no: e-copy only Record No: H048223)
(2.35 MB)
Proper utilization of water resources is very important in agro-based and drought-prone Bangladesh. Sustainable use of water resources in agriculture requires irrigation schedules based on local environmental conditions, soil type and water availability. In this study, the water productivity model AquaCrop was used to simulate different water and fertilizer management strategies in a drought prone area of Bangladesh to obtain management recommendations. First, the Standardised Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) were determined to quantify the aggregated deficit between precipitation and the evaporative demand of the atmosphere, which confirm that meteorological drought is occurring frequently in the study area. Also, the AquaCrop model was successfully calibrated and validated for wheat in the area, which was confirmed by the several statistical indicators, and could be used to design water and fertilizer management strategies. Simulations identified stem elongation (jointing) to booting and flowering stage as the most water sensitive stages for wheat. Deficit irrigation during the most water sensitive stages could increase the interannual yield stability and the grain yield compared to rainfed conditions for different soil fertility levels on loamy and sandy soils by 21–136% and 11–71%, respectively, while it could increase water productivity compared to full irrigation strategies. Deficit irrigation resulted in grain yields almost equal to yields under full irrigation and could at the same time save 121–197 mm of water per growing season. Specifically, we suggest two irrigation applications: one at the stem elongation (jointing) to booting stage and another at the flowering stage for loamy soils; and one at the end of seedling development to the beginning of crown root initiation stage and another at the flowering stage for sandy soils. Given the water scarcity in the region, instead of optimal fertility levels, moderate fertility levels are recommended that result in 60% of the potential biomass production for loamy soils and in 50% for sandy soils in combination with the suggested deficit irrigation strategies.
3 Moalafhi, D. B.; Sharma, A.; Evans, J. P. 2017. Reconstructing hydro-climatological data using dynamical downscaling of reanalysis products in data-sparse regions - application to the Limpopo Catchment in southern Africa. Journal of Hydrology: Regional Studies, 12:378-395. [doi: https://doi.org/10.1016/j.ejrh.2017.07.001]
Hydroclimatology ; Climatic data ; Models ; Simulation ; Meteorological observations ; Precipitation ; Temperature ; Arid climate ; Catchment areas ; River basins / Southern Africa / Limpopo Basin
(Location: IWMI HQ Call no: e-copy only Record No: H048295)
http://www.sciencedirect.com/science/article/pii/S2214581817302537/pdfft?md5=b8200e131bda5cfd71db88e4288c6253&pid=1-s2.0-S2214581817302537-main.pdf
https://vlibrary.iwmi.org/pdf/H048295.pdf
https://vlibrary.iwmi.org/pdf/H048295.pdf
(2.28 MB) (2.28 MB)
This study is conducted over the data-poor Limpopo basin centered over southern Africa using reanalysis downscaled to useful resolution.
Reanalysis products are of limited value in hydrological applications due to the coarse spatial scales they are available at. Dynamical downscaling of these products over a domain of interest offers a means to convert them to finer spatial scales in a dynamically consistent manner. Additionally, this downscaling also offers a way to resolve dominantatmospheric processes, leading to improved accuracy in the atmospheric variables derived. This study thus evaluates high-resolution downscaling of an objectively chosen reanalysis (ERA-I) over the Limpopo basin using Weather Research and Forecasting (WRF) as a regional climate model.
The model generally under-estimates temperature and over-estimates precipitation over the basin, although reasonably consistent with observations. The model does well in simulating observed sustained hydrological extremes as assessed using the Standardized Precipitation Index (SPI) although it consistently under-estimates the severity ofmoisture deficit for the wettest part of the year during the dry years. The basin's aridity index (I) is above the severe drought threshold during summer and is more severe in autumn. This practically restricts rain-fed agriculture to around 3 months in a year over the basin. This study presents possible beneficial use of the downscaled simulations foroptimal hydrologic design and water resources planning in data scarce parts of the world.
Reanalysis products are of limited value in hydrological applications due to the coarse spatial scales they are available at. Dynamical downscaling of these products over a domain of interest offers a means to convert them to finer spatial scales in a dynamically consistent manner. Additionally, this downscaling also offers a way to resolve dominantatmospheric processes, leading to improved accuracy in the atmospheric variables derived. This study thus evaluates high-resolution downscaling of an objectively chosen reanalysis (ERA-I) over the Limpopo basin using Weather Research and Forecasting (WRF) as a regional climate model.
The model generally under-estimates temperature and over-estimates precipitation over the basin, although reasonably consistent with observations. The model does well in simulating observed sustained hydrological extremes as assessed using the Standardized Precipitation Index (SPI) although it consistently under-estimates the severity ofmoisture deficit for the wettest part of the year during the dry years. The basin's aridity index (I) is above the severe drought threshold during summer and is more severe in autumn. This practically restricts rain-fed agriculture to around 3 months in a year over the basin. This study presents possible beneficial use of the downscaled simulations foroptimal hydrologic design and water resources planning in data scarce parts of the world.
4 Jury, M. R. 2017. Evaluation of satellite-model proxies for hydro-meteorological services in the upper Zambezi. Journal of Hydrology: Regional Studies, 13:91-109. [doi: https://doi.org/10.1016/j.ejrh.2017.08.003]
Meteorological observations ; Satellite observation ; Models ; Evaluation ; Hydrometeorology ; Monitoring ; Catchment areas ; Weather forecasting ; Flooding ; Rivers ; Discharges ; Rain ; Soil moisture ; Evaporation ; Valleys / Africa / Zambia / Upper Zambezi Catchment / Kafue Catchment
(Location: IWMI HQ Call no: e-copy only Record No: H048320)
http://www.sciencedirect.com/science/article/pii/S2214581816300763/pdfft?md5=3e89cedbb11f5b0a3091302e25193004&pid=1-s2.0-S2214581816300763-main.pdf
https://vlibrary.iwmi.org/pdf/H048320.pdf
https://vlibrary.iwmi.org/pdf/H048320.pdf
(3.96 MB) (3.96 MB)
Region: Upper Zambezi catchment and the river flow gauge at Kafue Hook (13.4S, 27.8E), typified by gentle topography and a strong seasonal cycle.
Focus: Evaluation of satellite and model estimates of hydro-meteorology conditions using data in the period 1998–2015, to supplement the very limited operational reports coming from the region.
Insights: Satellite soil moisture and model run-off track the Kafue Hook gauge with correlation values of 84% and 68%, respectively. Satellite river flow estimates achieve a logarithmic fit to monthly and daily gauge of 92% and 65%, respectively. Discrepancies are related to inadequate (calibration) reporting and to under-estimation of evaporation in the dry season. Statistical analyses of satellite rainfall and model evaporation are used to suggest improvements to hydro-meteorology network coverage in the upper Zambezi. An automated online network of ~20 weather stations and river flow gauges appears sufficient, given satellite-model ability to interpolate between observations.
Focus: Evaluation of satellite and model estimates of hydro-meteorology conditions using data in the period 1998–2015, to supplement the very limited operational reports coming from the region.
Insights: Satellite soil moisture and model run-off track the Kafue Hook gauge with correlation values of 84% and 68%, respectively. Satellite river flow estimates achieve a logarithmic fit to monthly and daily gauge of 92% and 65%, respectively. Discrepancies are related to inadequate (calibration) reporting and to under-estimation of evaporation in the dry season. Statistical analyses of satellite rainfall and model evaporation are used to suggest improvements to hydro-meteorology network coverage in the upper Zambezi. An automated online network of ~20 weather stations and river flow gauges appears sufficient, given satellite-model ability to interpolate between observations.
5 Shrestha, N. K.; Qamer, F. M.; Pedreros, D.; Murthy, M. S. R.; Wahid, S. M.; Shrestha, M. 2017. Evaluating the accuracy of Climate Hazard Group (CHG) satellite rainfall estimates for precipitation based drought monitoring in Koshi Basin, Nepal. Journal of Hydrology: Regional Studies, 13:138-151. [doi: https://doi.org/10.1016/j.ejrh.2017.08.004]
Meteorological observations ; Satellite observation ; Drought ; Rain ; Monitoring techniques ; Evaluation ; Precipitation ; Weather data ; Estimation ; Meteorological stations ; Mountains ; River basins / Nepal / Koshi Basin
(Location: IWMI HQ Call no: e-copy only Record No: H048329)
http://www.sciencedirect.com/science/article/pii/S2214581817300563/pdfft?md5=a0555e8065605f69522a60b59a4520d2&pid=1-s2.0-S2214581817300563-main.pdf
https://vlibrary.iwmi.org/pdf/H048329.pdf
https://vlibrary.iwmi.org/pdf/H048329.pdf
(1.64 MB) (1.64 MB)
Study region: Koshi basin, Nepal.
Study focus: While rainfall estimates based on satellite measurements are becoming a very attractive option, they are characterized by non-negligible biases. As such, we assessed the accuracy of two satellite products of the Climate Hazard Group (CHG) – (a) a satellite-only Climate Hazards Group InfraRed Precipitation (CHIRP) product, and (b) a CHIRP blended with ground-based station data (CHIRPS) – at a monthly time scale from 1981 to 2010 in the Koshi basin of Nepal using ground-based measurements. A separate analysis was also made for the data set after 1992, as the number of stations used in the blending has significantly reduced since 1992. Next, both CHG data sets were used to calculate one of the most popularly-used precipitation-based drought indicators – the Standardized Precipitation Index (SPI).
New hydrological insights for the study region: The accuracy of the CHG data set was found to be better in low-lying regions, while it was worse in higher-elevation regions. While the CHIRPS data set was better for the whole period, the CHIRP data set was found to be better for the period after 1992. Physiographic region-wise bias correction has improved the accuracy of the CHG products significantly, especially in higher-elevation regions. In terms of SPI values, the two CHG data sets indicated different drought severity when considering the whole period. However, the SPI values, and hence the drought severity were comparable when using the data from after 1992.
Study focus: While rainfall estimates based on satellite measurements are becoming a very attractive option, they are characterized by non-negligible biases. As such, we assessed the accuracy of two satellite products of the Climate Hazard Group (CHG) – (a) a satellite-only Climate Hazards Group InfraRed Precipitation (CHIRP) product, and (b) a CHIRP blended with ground-based station data (CHIRPS) – at a monthly time scale from 1981 to 2010 in the Koshi basin of Nepal using ground-based measurements. A separate analysis was also made for the data set after 1992, as the number of stations used in the blending has significantly reduced since 1992. Next, both CHG data sets were used to calculate one of the most popularly-used precipitation-based drought indicators – the Standardized Precipitation Index (SPI).
New hydrological insights for the study region: The accuracy of the CHG data set was found to be better in low-lying regions, while it was worse in higher-elevation regions. While the CHIRPS data set was better for the whole period, the CHIRP data set was found to be better for the period after 1992. Physiographic region-wise bias correction has improved the accuracy of the CHG products significantly, especially in higher-elevation regions. In terms of SPI values, the two CHG data sets indicated different drought severity when considering the whole period. However, the SPI values, and hence the drought severity were comparable when using the data from after 1992.
6 Qaiser, G.; Tariq, S.; Adnan, S.; Latif, M. 2021. Evaluation of a composite drought index to identify seasonal drought and its associated atmospheric dynamics in northern Punjab, Pakistan. Journal of Arid Environments, 185:104332. (Online first) [doi: https://doi.org/10.1016/j.jaridenv.2020.104332]
Drought ; Climate change ; Temperature ; Precipitation ; Monitoring ; Crop yield ; Normalized difference vegetation index ; Meteorological observations ; Moderate resolution imaging spectroradiometer / Pakistan / Punjab / Potwar Plateau / Islamabad / Attock / Chakwal / Jhelum / Rawalpindi
(Location: IWMI HQ Call no: e-copy only Record No: H050153)
(9.72 MB)
Drought is one of the most devastating climate extremes in terms of its spatial extent and intensity. Rainfed areas are extremely vulnerable to drought, but effective monitoring may lessen the impact of such events. This study developed a composite drought index (CDI) for monitoring and assessing seasonal droughts in rainfed areas of the Potwar Plateau of Pakistan, using remotely sensed and observed meteorological datasets. We identified four severe-to-extreme drought periods in the Rabi season (wheat; 2000–01, 2001–02, 2009–10, and 2011–12) and four such events in the Kharif season (maize; 2000–2002 and 2009). An intense agro-meteorological drought was experienced in 2000, which reduced the wheat and maize yields to -54.6% and -29.9%, respectively. Our analysis revealed that these conditions could be explained by the vertically integrated moisture flux divergence (MFD), moisture transport, and total precipitable water (TPW) anomalies. For example, the presence of a strong MFD anomaly over the study area was responsible for preventing moisture transport from the Arabian Sea and Bay of Bengal, resulting in dry conditions. The index developed here can effectively monitor seasonal droughts in rainfed areas, which may help inform strategies to lessen the impact of such events.
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