Water Level Index Research Articles

Drought Monitoring Methodology Based on AVHRR Images and SPOT Vegetation Maps

Many regions of the world are experiencing an increase in the frequency and intensity of droughts. The province of Fars, Iran, has faced particularly severe drought and ground water problems over the course of the last decade. However, previous research on the subject reveals a lack of useful information regarding droughts in this province. This paper presents a fast, efficient and reliable method that can be used to produce drought maps in which Advanced Very High Resolution Radiometer (AVHRR) images are processed and then compared with SPOT vegetation maps. Ten-day maximum Normalized Difference Vegetation Index (NDVI) maps were produced and vegetation drought indices such as the Vegetation Condition Index (VCI) were calculated. Furthermore, a Temperature Condition Index (TCI) was extracted from the thermal bands of AVHRR images in order to produce the Vegetation Health Index (VHI). Remotely sensed data was then compared with hydrological and meteorological data from 1998 to 2007. The Standardized Precipitation Index (SPI) was used to quantify the precipitation deficit while the Standard Water Level Index (SWI) was developed to assess the groundwater recharge deficit. Instead of correlation coefficients, spatial correlation through visual comparison was found to provide better and more meaningful pictures. The highest correlation values were obtained when VHI or Drought Severity Index (DSI) values were correlated with the current month’s SWI data. DSI maps showed strong vegetation conditions existing for the majority of the study period. For most counties in Fars, strong Pearson correlations observed between the DSI and the SWI of the same month reflect high rates of ground water consumption. The results of this study indicate that the proposed method is a potentially promising method for early drought awareness which can be used for drought risk management in semi-arid climates such as in Fars, Iran. This study also recommends that the Iranian government develop programs to help decrease the consumption of ground water resources in the province of Fars to ensure the long term sustainability of the watersheds in this province.

Multireservoir real-time operations for flood control using balanced water level index method

This paper presents a real-time simulation-optimization operation procedure for determining the reservoir releases at each time step during a flood. The proposed procedure involves two models, i.e., a hydrological forecasting model and a reservoir operation model. In the reservoir operation model, this paper compares two flood-control operation strategies for a multipurpose multireservoir system. While Strategy 1 is the real-time joint reservoir operations without using the balanced water level index (BWLI) method, Strategy 2 involves real-time joint reservoir operations using the BWLI method. The two strategies presented are formulated as mixed-integer linear programming (MILP) problems. The idea of using the BWLI method is derived from the HEC-5 program developed by the US Army Corps of Engineers. The proposed procedure has been applied to the Tanshui River Basin system in Taiwan using the 6 h ahead forecast data of six typhoons. A comparison of the results obtained from the two strategies reveals that Strategy 2 performs much better than Strategy 1 in determining the reservoir real-time releases throughout the system during flood emergencies in order to minimize flooding, while maintaining all reservoirs in the system in balance if possible. Consequently, the proposed model using the BWLI method demonstrates its effectiveness in estimating real-time releases.

Monitoring drought dynamics in the Aravalli region (India) using different indices based on ground and remote sensing data

The hard-rock hilly Aravalli terrain of Rajasthan province of India suffers with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. In the present study, detailed analysis of meteorological and hydrological data of the Aravalli region has been carried out for the years 1984–2003. Standardised Precipitation Index (SPI) has been used to quantify the precipitation deficit. Standardised Water-Level Index (SWI) has been developed to assess ground-water recharge-deficit. Vegetative drought indices like Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) and Vegetation Health Index (VHI) have been computed using NDVI values obtained from Global Vegetation Index (GVI) and thermal channel data of NOAA AVHRR satellite. Detailed analyses of spatial and temporal drought dynamics during monsoon and non-monsoon seasons have been carried out through drought index maps generated in Geographic Information Systems (GIS) environment. Analysis and interpretation of these maps reveal that negative SPI anomalies not always correspond to drought. In the Aravalli region, aquifer-stress shifts its position time to time, and in certain pockets it is more frequent. In comparison to hydrological stress, vegetative stress in the Aravalli region is found to be slower to begin but quicker to withdraw.

Distribution of Wading Birds Relative to Vegetation and Water Depths in the Northern Everglades of Florida, USA

The response of Great Blue Herons (Ardea herodias), Great Egrets (Casmerodius albus), Wood Storks (Mycteria americana), and White Ibises (Eudocimus albus) to water level (index of depth) and vegetation in the northern Everglades of Florida was studied in two years, each with dissimilar water levels. A regression model was constructed for each species in an average year (1988) and a dry year (1989) to examine the relationship of bird abundance to water depth and area of eight vegetation classes. The analyses showed that bird abundance is related to both water level and the vegetation community, but water level generally had the greatest effect. Models showed that in the average year (1988), there was a water level threshold, above which bird abundance was predicted to decline. The level threshold varied among species and may have reflected species-specific foraging constraints. However, in the dry year (1989), the relationship between bird abundance and water level was positive and linear, indicating that few places had water deeper than the thresholds observed in the average year. Overall, the area of slough vegetation appeared to have the second greatest effect on bird abundance. Generally, all models had low coefficients of determination (R2 range 0.06-0.42) suggesting that factors other than water level and vegetation were important, or birds were responding to variables in the model, but at different spatial scales than that which the data were collected. Models for Great Blue Herons and Great Egrets had higher coefficients of determination than models for Wood Storks and White Ibises. The more solitary feeding behavior of the herons and egrets resulted in a more even distribution across the marsh than for storks and ibises, which were usually found in flocks. Our study suggests that if restoration of the Everglades results in more natural hydrologic cycles, an increase in the amount of slough habitat, and a decrease in the proportion of cattails, foraging conditions for wading birds may improve.

A FORAMINIFERAL-BASED TRANSFER FUNCTION: IMPLICATIONS FOR SEA-LEVEL STUDIES

A dataset consisting of 165 contemporary foraminiferal samples and associated tide level information was compiled by combining data from ten intertidal study areas situated on the east, south and west coasts of the UK. The relationship between the foraminiferal data and a series of environmental variables (elevation, pH, salinity, substrate and vegetation cover) are examined using canonical correspondence analysis (CCA) and partial CCA. To facilitate comparisons between study areas with different tidal ranges, the elevational data are expressed as a standardised water level index (SWLI). The foraminiferal distributions show a strong and highly statistically significant relationship with SWLI. A predictive transfer function has been developed for SWLIs using weighted averaging calibration with inverse and classical deshrinking regression (inverse r 2 jack = 0.74; classical r 2 jack = 0.75). Statistical measures assessing the performance of this model suggest that reliable reconstructions of former sea levels are possible. The transfer function has important implications for establishing continuous records of relative sea-level change or sedimentation.