Drought Forecasting in a Semi-arid Watershed Using Climate Signals:a Neuro-fuzzy Modeling Approach

Large-scale annual climate indices were used to forecast annual drought conditions in the Maharlu-Bakhtegan watershed,located in Iran,using a neuro-fuzzy model.The Standardized Precipitation Index（SPI） was used as a proxy for drought conditions.Among the 45 climate indices considered,eight identified as most relevant were the Atlantic Multidecadal Oscillation（AMO）,Atlantic Meridional Mode（AMM）,the Bivariate ENSO Time series（BEST）,the East Central Tropical Pacific Surface Temperature（NINO 3.4）,the Central Tropical Pacific Surface Temperature（NINO 4）,the North Tropical Atlantic Index（NTA）,the Southern Oscillation Index（SOI）,and the Tropical Northern Atlantic Index（TNA）.These indices accounted for 81% of the variance in the Principal Components Analysis（PCA） method.The Atlantic surface temperature（SST：Atlantic） had an inverse relationship with SPI,and the AMM index had the highest correlation.Drought forecasts of neuro-fuzzy model demonstrate better prediction at a two-year lag compared to a stepwise regression model.     

An Integrated GIS Based Statistical Model to Compute Groundwater Vulnerability Index for Decision Maker in Agricultural Area

The conservation areas in a plain are affected by the groundwater contamination from intense application of the fertilizers. The vulnerability of groundwater can be tested by using the DRASTIC model for the pollutants. The groundwater susceptibility to pollution in the various areas is mapped through DRASTIC model. However, the effects of pollution types and its characteristics are not considered, as this model is used without any modifications. This technique must be standardized for usage in the various aquifers and specific pollution types. The rates of DRASTIC parameters are corrected to obtain the potential for a more accurate analysis of the vulnerability pollution. The relationships between the parameters are identified with respect to the nitrate concentration in the groundwater by calculating the new rates. The methodology was applied to the selected area situated in the south eastern region of Iran at Kerman plain. Twenty-seven different locations were selected to test and analyse the nitrate concentration in the water from underground wells. The pollution in the aquifer was associated and correlated with the DRASTIC index by using the measured nitrate concentrations. The relationship between the index and the measured pollution in the Kerman plain was determined by applying the Wilcoxon rank-sum nonparametric statistical tests and the rates were calculated. It was found specifically in the agricultural areas that the modified DRASTIC model performed more efficiently than the traditional method for nonpoint source pollution, as indicated by the results. After modifications, the regression coefficients revealed that the relationship between the vulnerability index and the nitrate concentration was 77 %, while it was 37 % before the modifications were used. These statistics show that the modified DRASTIC performed far more efficiently than the original version.     

A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf

Diffuse attenuation coefficient (k _d ) is a critical parameter for benthic habitat mapping using remotely sensed data. This research attempted to develop a new approach to estimate k _d in blue and green bands of QuickBird satellite image based on the integration of Lyzenga’s method and updated NASA-k _d ⁴⁹⁰ algorithm. To do this, the Lyzenga’s method was utilized to determine the ratio of k _d in different bands of QuickBird satellite image. Additionally, NASA-k _d ⁴⁹⁰ algorithm was applied to determine k _d ⁴⁹⁰ by using remotely sensed reflectance values of blue (R _rs ^Blue ) and green (R _rs ^Green ) bands in each pixel of QuickBird satellite image. Since the aforementioned algorithm has been developed for other types of sensors, an approach using weighted mean value of parameters for SeaWiFS, MERIS, VIIRS, and OCTS sensors were employed to estimate parameter values for QuickBird image. After determining the k _d ⁴⁹⁰ values as k _d for blue band, the k _d values for green and red bands were subsequently obtained by using Lyzenga’s method. Then, Mumby and Edwards’ method was employed as evidence to evaluate the accuracy of the results achieved from newly developed approach. Eventually, the maximum likelihood classifier was implemented during pre and post correction steps to examine the capability of the proposed approach. The final results proved to be consistent in the areas deeper than 2 m between estimated k _d values using the proposed approach and the results obtained from Mumby and Edwards’ method. On the other hand, the values estimated for extremely shallow areas seem to be overestimated. Furthermore, results demonstrated an increment of ~16 % in the overall accuracy of the classification.     

Risk assessment of soil erosion in semi-arid mountainous watershed in Saudi Arabia by RUSLE model coupled with remote sensing and GIS

Soil erosion is the most important factor in land degradation and influences desertification in semi-arid areas. A comprehensive methodology that integrates revised universal soil loss equation (RUSLE) model and GIS was adopted to determine the soil erosion risk (SER) in semi-arid Aseer region, Saudi Arabia. Geoenvironmental factors viz. rainfall (R), soil erodibility (K), slope (LS), cover management and practice factors were computed to determine their effects on average annual soil loss. The high potential soil erosion, resulting from high denuded slope, devoid of vegetation cover and high intensity rainfall, is located towards the north western part of the study area. The analysis is investigated that the SER over the vegetation cover including dense vegetation, sparse vegetation and bushes increases with the higher altitude and higher slope angle. The erosion maps generated with RUSLE integrated with GIS can serve as effective inputs in deriving strategies for land planning/management in the environmentally sensitive mountainous areas.     

Remote sensing for change detection in the Sunderbands,Bangladesh

Abstract

Change detection study has been made for the mangrove forest of the Sunderbans (Bangladesh) using remote sensing and other ancillary data (1933–1987). At the advent of the British rule the forest was double their present extent. Its present area is about 6000.0 Sq. Km. The productive land area has been increased from 1960. Gewa (Excoecaria agallocha)‐Sundri (Heritiera fames) cover type areas have been increased at the expense of pure Sundri type. Height classes of the forest have been changed, basal area/ha has decreased. It is observed that there is a net decrease in Sundri standing volume of the order of 40% and that of Gewa 45% over the past 25 years (1960–1985). Total timber volume for all of the species has been reduced to near about a half. Timber volume/ha and basal area/ha for Gewa have increased in the Sharankhola Island of the forest. Sundri tress are being replaced by Gewa. CIR aerial photographs have been found most suitable for cover type analysis and other change detection study. Regular monitoring of the changes of the forest using remote sensing technique has been suggested.     

Snow and stream-water chemistry of the Ganga headwater basin,Garhwal Himalaya,India

Abstract

Studies of the chemical composition of snowpack and stream water were carried out in a catchment having an area of 53km² (31°03′-30°55′N and 78°40′-78°51′E) in the Garhwal Himalaya, India. The dominant ions in the snowpack and stream water were Ca²⁺, Na⁺, NO^? ₃, SO^2- ₄ and HCO^? ₃. Solute patterns in the snowpack show preferential elution. Investigation of the chemical composition of stream water shows that meltwater changes its composition substantially as it passes through soil pathways to the stream. The groundwater flushing perhaps controls the chemical composition of meltwater in the early spring. However, in the period from July to September, the stream water carries the chemical signature of monsoonal precipitation.     

Temperature variability caused by internal tides in the coastal waters of east coast of Peninsular Malaysia

The effects of tidal currents (i.e., barotropic and internal tides) are important in the biogeochemistry of a coastal shelf sea. The high-frequency of currents and near-bottom temperatures collected in three consecutive southwest monsoon seasons (May, June, July and August of 2013 until 2015) is presented to reveal the role of the tidal currents to the temperature variability in the coastal shelf sea of the east coast of Peninsular Malaysia (ECPM), south of the South China Sea (SCS). The results of a spectral density and harmonic analysis demonstrate that the near-bottom temperature variability and the tidal currents are influenced by diurnal (O₁ and K₁) and semidiurnal (M₂) tidal currents. The spectral density of residual currents (detided data) at 5, 10 and 16 m depth also shows significant peaks at the diurnal tidal frequency (K₁) and small peaks at the semidiurnal tidal frequency (M₂) indicating the existence of internal tides. The result of the horizontal kinetic energy (HKE) shows a strong intermittent energy of internal tides in the ECPM with the strongest energy is found at 16 m depth during a sporadic cooling event in June and July. A high horizontal cross-shore heat flux (16 m) also indicates strong intrusions of cooler water into the ECPM in June and July. During the short duration of cold pulse water observed in June and July, a cross-wavelet analysis also reveals the strong relationship between the near-bottom temperatures and the internal tidal currents at the diurnal tidal frequency. The intrusion of this cooler water is probably related to the monsoon-induced upwelling in June. It is loosely interpreted that the interaction between the strong barotropic tides and the steep slope in the central basin of the SCS under the stratified condition in southwest monsoon has generated these internal tides. The dissipation of internal tides from the slope area probably has driven the cold-upwelled water into the ECPM coastal shelf sea when the upwelling intensity is the highest in June and July.     

Solar forcing on antarctic terrestrial climate: A study by means of GPS observations

With a view to difficulties with explaining the physical mechanism of solar forcing on the Earth’s climate, we applied a new approach of determining and quantifying an influence of solar-related events on water vapor variability by correlating the total electron content (TEC) and precipitable water vapor (PWV), both derived from ground-based GPS observations. In this study, ionospheric TEC and atmospheric PWV values are employed as solar activity and terrestrial climate parameters, respectively. Three-year GPS data at five stations in Antarctica are analyzed on a daily mean basis. Results show significant correlation between TEC and PWV differences during storms-affected days. The high correlation between the daily mean values of TEC and PWV, both of which follow the seasonal signals and subsisting downward trend, suggests an influence of solar activity on climate variability in Antarctica. These quantities are determined by changes of the upper-atmosphere level, which varies in conformity with the zenith angle of the Sun.