Drought monitoring represents a challenge for water and agricultural sector as this natural hazard accelerates water deficiency and leads to adverse environmental and socioeconomic impacts. The use of remote sensing d...Drought monitoring represents a challenge for water and agricultural sector as this natural hazard accelerates water deficiency and leads to adverse environmental and socioeconomic impacts. The use of remote sensing data and geospatial techniques to monitor and map drought severity expanded in the last decades with progressive developments in data sources and processing. This study investigates the correlations among drought indices derived with soil moisture stress (K) obtained from ground data collected from fields cultivated with barley. The study, carried out in Yarmouk basin in the north of Jordan, includes NDVI, PDI, MPDI and PVI derived from Landsat 8-OLI and Sentinel 2-MSI. Results showed different behavior among the indices and throughout the 2016/2017 growing season, with maximum correlation between PDI and MPDI followed by NDVI with PVI. Correlations among the remote sensing indices and K for different soil depths during March-April were significant for most indices with a maximum (R2) of 0.82 for K30-50 and MPDI, followed by K30-50 with NDVI. Drought severity maps for the month of March showed different trends for the different indices, with similarities between MPDI and PDI. The map of drought severity combined from the remote sensing indices and K showed that PDI and soil moisture could significantly explain 56% of variations in spatial patterns of drought, while the combination of MPDI, PDI and NDVI could significantly explain up to 59% of variations in drought severity map. Therefore, the study recommends the adoption of these remotely sensed indices for monitoring and mapping of agricultural droughts.展开更多
Groundwater resources in Jordan are under huge stresses. Accomplishing good water quality requires monitoring of water resources. Azraq spring considered the main source for drinking water of Fuhais City in Balqa gove...Groundwater resources in Jordan are under huge stresses. Accomplishing good water quality requires monitoring of water resources. Azraq spring considered the main source for drinking water of Fuhais City in Balqa governorate. The catchment area of the spring is less than 23 km2 and forms part of the side wadis feeding the groundwater basin in wadi Shuaib. This study aims to assess the vulnerability of groundwater to pollution that may result from agricultural activities and Fuhais wastewater treatment plant using GIS and DRASTIC model functions. Each symbol of the DRASTIC refers to one of the seven DRASTIC model parameters: Depth to water (D), Net recharge (R), Aquifer formation (A), Soil (S), Topography or slope (T), Impact of vadose zone (I) and Hydraulic conductivity (C). The final map of vulnerability showed 5 classes with different percent for each. These were: very low (5%), low (16%), moderate (11%), high (34%) and very high (34%). In terms of area, the high and very high vulnerability classes distributed over 7.75 Km2, while the low vulnerability distributed over 1.10 Km2. Implementation of DRASTIC model showed increasing the vulnerability of ground water to contamination in the western part of study area because of the vadose zone and due to soil properties in this part of the study area. As such, vulnerability to pollution increased from the upstream area, where the treatment plant is located to the downstream area following the direction of flow and according to permeability. Water depth, net-recharge and media of aquifer had neglected effect of vulnerability map because it had one value at overall study area for each one. DRASTIC parameters could be arranged according to its effect on vulnerability map as I > S > C > T > (D = R = A).展开更多
文摘Drought monitoring represents a challenge for water and agricultural sector as this natural hazard accelerates water deficiency and leads to adverse environmental and socioeconomic impacts. The use of remote sensing data and geospatial techniques to monitor and map drought severity expanded in the last decades with progressive developments in data sources and processing. This study investigates the correlations among drought indices derived with soil moisture stress (K) obtained from ground data collected from fields cultivated with barley. The study, carried out in Yarmouk basin in the north of Jordan, includes NDVI, PDI, MPDI and PVI derived from Landsat 8-OLI and Sentinel 2-MSI. Results showed different behavior among the indices and throughout the 2016/2017 growing season, with maximum correlation between PDI and MPDI followed by NDVI with PVI. Correlations among the remote sensing indices and K for different soil depths during March-April were significant for most indices with a maximum (R2) of 0.82 for K30-50 and MPDI, followed by K30-50 with NDVI. Drought severity maps for the month of March showed different trends for the different indices, with similarities between MPDI and PDI. The map of drought severity combined from the remote sensing indices and K showed that PDI and soil moisture could significantly explain 56% of variations in spatial patterns of drought, while the combination of MPDI, PDI and NDVI could significantly explain up to 59% of variations in drought severity map. Therefore, the study recommends the adoption of these remotely sensed indices for monitoring and mapping of agricultural droughts.
文摘Groundwater resources in Jordan are under huge stresses. Accomplishing good water quality requires monitoring of water resources. Azraq spring considered the main source for drinking water of Fuhais City in Balqa governorate. The catchment area of the spring is less than 23 km2 and forms part of the side wadis feeding the groundwater basin in wadi Shuaib. This study aims to assess the vulnerability of groundwater to pollution that may result from agricultural activities and Fuhais wastewater treatment plant using GIS and DRASTIC model functions. Each symbol of the DRASTIC refers to one of the seven DRASTIC model parameters: Depth to water (D), Net recharge (R), Aquifer formation (A), Soil (S), Topography or slope (T), Impact of vadose zone (I) and Hydraulic conductivity (C). The final map of vulnerability showed 5 classes with different percent for each. These were: very low (5%), low (16%), moderate (11%), high (34%) and very high (34%). In terms of area, the high and very high vulnerability classes distributed over 7.75 Km2, while the low vulnerability distributed over 1.10 Km2. Implementation of DRASTIC model showed increasing the vulnerability of ground water to contamination in the western part of study area because of the vadose zone and due to soil properties in this part of the study area. As such, vulnerability to pollution increased from the upstream area, where the treatment plant is located to the downstream area following the direction of flow and according to permeability. Water depth, net-recharge and media of aquifer had neglected effect of vulnerability map because it had one value at overall study area for each one. DRASTIC parameters could be arranged according to its effect on vulnerability map as I > S > C > T > (D = R = A).
