ANALISIS HUBUNGAN KEKERINGAN METEOROLOGIS DENGAN KEKERINGAN AGRIKULTURAL DI PULAU LOMBOK MENGGUNAKAN KORELASI PEARSON

One of the disasters can cause losses in various sectors and have an impact on people's lives is drought. Lombok Island is an area with a high risk of drought. The Standardized Precipitation Index (SPI) describes meteorological drought using rainfall as the main parameter. The Normalized Differences Vegetation Index (NDVI) describes agricultural drought based on remote sensing. This research aims to determine the relationship between SPI using the reanalysis rainfall data Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) with observed rainfall (CH Obs) and NDVI at 22 rain observation stations on Lombok Island during the 2001 – 2018. The use method is to calculate the Pearson correlation and the significance of SPI with CH Obs and NDVI. The correlation between SPI with CH Obs and NDVI is positive and significant, respectively 0.31 and 0.21 with p-value <0.05. This illustrates that drought monitoring using reanalysis and remote sensing data can be done because it describes the actual drought in the study area. In addition, it can be concluded that the meteorological drought that occurred could have an impact on agricultural drought in the Lombok during 2001 - 2018

Evaluation of Remotely Sensed Precipitation Estimates from the NASA POWER Project for Drought Detection Over Jordan

Droughts can cause devastating impacts on water and land resources and therefore monitoring these events forms an integral part of planning. The most common approach for detecting drought events and assessing their intensity is use of the Standardized Precipitation Index (SPI), which requires abundant precipitation records at good spatial distribution. This may restrict SPI usage in many regions around the world, particularly in areas with limited numbers of ground meteorological stations. Therefore, the use of remotely sensed derived data of precipitation can contribute to drought monitoring. In this study, remotely sensed precipitation estimates from the POWER/Agroclimatology archive of NASA and their derived SPI for different time intervals were evaluated against gauged observations of precipitation from 13 different stations in arid and semiarid locations in Jordan. Results showed significant correlations between remotely sensed and ground data with relatively high R values (0.67–0.91), particularly where seasonal precipitation exceeded 50 mm/year. For evaluation of remotely sensed data in SPI calculation, several objective functions were used; the results showed that SPI based on satellite estimates (SAT-SPI) showed good performance in detecting extreme droughts and indicating wet/dry conditions. However, SAT-SPI showed high tendency to overestimate drought intensity. Based on these findings, remotely sensed precipitation from the POWER/Agroclimatology archive showed good potential for use in detecting extreme meteorological drought with the provision of careful interpretation of the data. These types of studies are essential for evaluating the applicability of new drought monitoring information and tools to support decision-making at relevant scales

Quantifying land use heterogeneity on drought conditions for mitigation strategies development in the Dongjiang River Basin, China

Spatially-invariant land use and cover changes (LUCC) are not suitable for managing non-stationary drought conditions. Therefore, developing a spatially varying framework for managing land resources is necessary. In this study, the Dongjiang River Basin in South China is used to exemplify the significance of spatial heterogeneity in land planning optimization for mitigating drought risks. Using ERA5 that is the 5th major atmospheric reanalysis from the European Centre for Medium-Range Weather Forecast, we computed the Standardized Runoff Index (SRI) to quantify the hydrologic drought during 1992 to 2018. Also, based on Climate Change Initiative land use product, The Geographically Weighted Principal Component Analysis was used to identify the most dominant land types in the same period. Then, we used the Emerging Hot Spots Analysis to characterize the spatiotemporal evolution of historical LUCC and SRI. The spatially varying coefficients of Geographically and Temporally Weighted Regression models were used to reveal the empirical relationships between land types and the SRI. Results indicated that rainfed cropland with herbaceous cover, mosaic tress and shrub, shrubland, and grassland were four land types having statistical correlations with drought conditions over 27 years. Moreover, since 2003, the DRB was becoming drier, and the northern areas generally experienced severer hydrologic drought than the south. More importantly, we proposed region-specific land-use strategies for drought risk reductions. At a basin scale, we recommended to 1) increase rainfed herbaceous cropland and 2) reduce mosaic tree and shrub. At a sub-basin scale, the extents of shrub and grassland were suggested to increase in the northern DRB but to reduce in the south. Region-specific land use planning, including suitable locations, scales, and strategies, will contribute to handling current ‘one-size-fits-all’ LUCC. Planners are suggested to integrate spatial characteristics into future LUCC for regional hydrologic management

The Temporal-Spatial Characteristics of Drought in the Loess Plateau Using the Remote-Sensed TRMM Precipitation Data from 1998 to 2014

Rainfall gauges are always sparse in the arid and semi-arid areas of Northwest China, which makes it difficult to precisely study the characteristics of drought at a large scale in this region and similar areas. This study used the TRMM (The Tropical Rainfall Measuring Mission) multi-satellite precipitation data to study the spatial-temporal evolution of drought in the Loess Plateau based on the SPI (Standardized Precipitation Index) drought index for the period of 1998&ndash;2014. The results indicate that the monthly TRMM precipitation data are well matched with the observed precipitation, indicating that this remotely sensed data set can be reliably used to calculate the SPI drought index. Based on the study findings, the average precipitation in the Loess Plateau is showing a significant increasing trend at the rate of 4.46 mm/year. From the spatial perspective, the average annual precipitation in the Southeast is generally greater than that in the Northwest. However, the annual precipitation in the Southeast area is showing a decreasing trend, whereas, the annual precipitation in the northwest areas is showing an increasing trend. Through the SPI analysis, the 3-month SPI and 12-month SPI were both showing an increasing trend, which indicates that the drought severity in the Loess Plateau was a generally declining trend at a seasonal to annual time scale. From the spatial perspective, the SPI values in the Central and Northwest of the Loess Plateau were significantly increasing, whereas, the SPI values in the southern area of the Loess Plateau were slightly decreasing. From the seasonal characteristics, the high-risk area for drought in the spring was concentrated in the northeast and southwest part, and in the summer and autumn, the high-risk area was transferred to the south part. Through this study, it is concluded that the Loess Plateau was likely getting wetter during the time period since the Grain-for-Green Project (1999&ndash;2012) was implemented, which replaced much farmland with forestry. This is a positive signal for vegetation recovery and ecological restoration in the near future

The Temporal-Spatial Characteristics of Drought in the Loess Plateau Using the Remote-Sensed TRMM Precipitation Data from 1998 to 2014

Rainfall gauges are always sparse in the arid and semi-arid areas of Northwest China, which makes it difficult to precisely study the characteristics of drought at a large scale in this region and similar areas. This study used the TRMM (The Tropical Rainfall Measuring Mission) multi-satellite precipitation data to study the spatial-temporal evolution of drought in the Loess Plateau based on the SPI (Standardized Precipitation Index) drought index for the period of 1998-2014. The results indicate that the monthly TRMM precipitation data are well matched with the observed precipitation, indicating that this remotely sensed data set can be reliably used to calculate the SPI drought index. Based on the study findings, the average precipitation in the Loess Plateau is showing a significant increasing trend at the rate of 4.46 mm/year. From the spatial perspective, the average annual precipitation in the Southeast is generally greater than that in the Northwest. However, the annual precipitation in the Southeast area is showing a decreasing trend, whereas, the annual precipitation in the northwest areas is showing an increasing trend. Through the SPI analysis, the 3-month SPI and 12-month SPI were both showing an increasing trend, which indicates that the drought severity in the Loess Plateau was a generally declining trend at a seasonal to annual time scale. From the spatial perspective, the SPI values in the Central and Northwest of the Loess Plateau were significantly increasing, whereas, the SPI values in the southern area of the Loess Plateau were slightly decreasing. From the seasonal characteristics, the high-risk area for drought in the spring was concentrated in the northeast and southwest part, and in the summer and autumn, the high-risk area was transferred to the south part. Through this study, it is concluded that the Loess Plateau was likely getting wetter during the time period since the Grain-for-Green Project (1999-2012) was implemented, which replaced much farmland with forestry. This is a positive signal for vegetation recovery and ecological restoration in the near future

The Temporal-Spatial Characteristics of Drought in the Loess Plateau Using the Remote-Sensed TRMM Precipitation Data from 1998 to 2014

Rainfall gauges are always sparse in the arid and semi-arid areas of Northwest China, which makes it difficult to precisely study the characteristics of drought at a large scale in this region and similar areas. This study used the TRMM (The Tropical Rainfall Measuring Mission) multi-satellite precipitation data to study the spatial-temporal evolution of drought in the Loess Plateau based on the SPI (Standardized Precipitation Index) drought index for the period of 1998&ndash;2014. The results indicate that the monthly TRMM precipitation data are well matched with the observed precipitation, indicating that this remotely sensed data set can be reliably used to calculate the SPI drought index. Based on the study findings, the average precipitation in the Loess Plateau is showing a significant increasing trend at the rate of 4.46 mm/year. From the spatial perspective, the average annual precipitation in the Southeast is generally greater than that in the Northwest. However, the annual precipitation in the Southeast area is showing a decreasing trend, whereas, the annual precipitation in the northwest areas is showing an increasing trend. Through the SPI analysis, the 3-month SPI and 12-month SPI were both showing an increasing trend, which indicates that the drought severity in the Loess Plateau was a generally declining trend at a seasonal to annual time scale. From the spatial perspective, the SPI values in the Central and Northwest of the Loess Plateau were significantly increasing, whereas, the SPI values in the southern area of the Loess Plateau were slightly decreasing. From the seasonal characteristics, the high-risk area for drought in the spring was concentrated in the northeast and southwest part, and in the summer and autumn, the high-risk area was transferred to the south part. Through this study, it is concluded that the Loess Plateau was likely getting wetter during the time period since the Grain-for-Green Project (1999&ndash;2012) was implemented, which replaced much farmland with forestry. This is a positive signal for vegetation recovery and ecological restoration in the near future