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• A Spatially Distributed Event-Based Model to Predict Sediment Yield
  Sreenivas Kandrika^* and Venkataratnam, L., Agriculture & Soils Group, National Remote Sensing Agency, (Department of Space, Govt. of India), Balanagar, Hyderabad – 500 037, India.

  Abstract: A study has been conducted in three sub-watersheds to model the spatial distribution of runoff and sediment yield. The basic structure of the model includes generation of runoff using SCS curve number (CN) method and soil detachment by RUSLE, MUSS and MUST equations, which is in turn delimited by Kirkby’s transport capacity equation. The input parameter grids – cover, practice and soil erodibility grids were generated from satellite data with adequate field check. Routing of runoff and sediment was done in ARC/INFO’s GRID module. Predicted results were validated with field-measured values. Results show that the runoff from CN method was better estimated after accounting for depression storage. Results from two hilly watersheds show that the standard error of sediment yield prediction of RUSLE < MUSS < MUST equations. In a relatively flat watershed, sediment yields were underestimated, due to underestimation of transport capacity. Hence, there is a need to address the transport capacity in plains and moderately sloping areas.

  Keywords: Runoff, sediment yield, GIS, remote sensing, watershed, event-based.
   

• Performances of Stochastic Approaches in Generating Low Streamflow Data for Drought Analysis
  Kadri YUREKLI and Ahmet KURUNC, Gaziosmanpasa Unıversity, Faculty of Agriculture, Department of Agricultural Technology 60250 Tasliciftlik-Tokat/TURKEY.
  
  Abstract: This study analyzed the monthly-minimum daily discharge data of each month from three gauge stations on Cekerek Stream for forecasting using stochastic approaches. Initially non-parametric test (Mann-Kendall) was used to identify the trend during study period. The two approaches of stochastic modeling, ARIMA and Thomas-Fiering models, were used to simulate the monthly-minimum daily discharge data of each month. The error estimates (RMSE and MAE) of forecasts from both approaches were compared to identify the most suitable approach for reliable forecast. The two error estimates calculated for two approaches indicate that ARIMA model appear to be slightly better than Thomas-Fiering. However, both approaches were identified as appropriate method for simulating the monthly-minimum daily discharge data of each month from three gauge stations on Cekerek Stream.

  Key words: monthly-minimum daily discharge, stochastic model, ARIMA, Thomas-Fiering
   

• Spatial Analysis of Urban Stormwater Quality
  M. Ghafouri¹ and C.E. Swain, 1. School of Engineering and Technology, Deakin University, Geelong, Vic, 3217, Australia, amrouzbe@deakin.edu.
  
  Abstract: Urban stormwater non-point source pollutants are recognized as a major cause of receiving waters quality deterioration. To date most research has focused on specifying temporal variations of stormwater quality parameters which includes high uncertainties and also increases the risk of pollution control structures failure. Traditionally, the temporal variations of quality parameters in forms of either pollutograph or Event Mean Concentration (EMC) is obtained by sampling stormwater at the outlet of urban catchments for quality analysis in addition to measurement of flow rate over years. Spatial variations of the runoff quality are the key factor in non-point source pollution studies. This research investigates spatial variability of urban runoff quality parameters such as Total Phosphorous (TP), Total Nitrogen (TN), Suspended Solids (SS) and Biochemical Oxygen Demands (BOD) in relation to land use of urban catchments. In spatial analysis, stormwater will be sampled over the whole catchment area for a number of rainfall events during a year without any requirement to measure flow rate. This research showed comparable results for average pollutant concentrations with those of other urban catchments in Australia where traditional sampling method was used. The research outcomes will reliably estimate pollutants concentration for improved and efficient design of pollution control structures for each land use.

  Keywords: Spatial analysis, temporal analysis, stormwater, Event Mean Concentration, geostatistics, pollutants
   

• Spatial Modeling for Hydrological Response Behavior of an Arid Watershed, India - Remote Sensing and GIS approach Debashis Chakraborty¹, Dibyendu Dutta² and H Chandrasekharan³, ¹Division of Agricultural Physics, Indian Agricultural Research Institute, NewDelhi – 110 012, INDIA. E-mail: debashis@iari.res.in  / debashisiari@hotmail.com , ²Regional Remote Sensing Service Centre (ISRO/DOS), CAZRI Campus, Jodhpur 342 003, India., ³Water Technology Centre, Indian Agricultural Research Institute, New Delhi 110 012, INDIA
  
  Abstract: The paper discusses the applications of satellite remote sensing and GIS on characterization and spatial modeling of runoff and soil erosion of Birantiya Kalan, an arid watershed in the district of Pali, western Rajasthan. The watershed, with plains on the west and low to medium hills on the east, is among the watersheds selected under the National Watershed Development Project for Rainfed Areas by the Government of India in 1988. Indian Remote Sensing Satellite Data (IRS 1A/1B LISS II sensor) corresponding to pre-treatment (1988) and post-treatment (1996) periods were used to study changes in the land use/ land cover and vegetation status of the watershed. Suitable weightages were given for the relative response of different land use categories and vegetation types to various soil and water conservation measures adopted under the said project over the years (1988-1996). Composite values computed for land use/ land cover and changes in vegetation vigour indicated a marginal improvement during the period of study. Morphometric analysis revealed that the watershed might produce moderate to peak runoff in a short period. SCS Curve Number method and Universal Soil Loss Equation were applied with ARC/INFO-GIS to predict the potential runoff and soil erosion status of the watershed. An average of 50-70 mm (equivalent of 20-30 per cent of the rainfall) runoff was predicted. Soil erosion potential was found to be below the permissible limit and increase in the runoff and soil erosion potential was observed in 1996. Apart from using land use and vegetation vigour information, drainage buffer region was created to quantify the status of vegetation along drains. This approach, coupled with analyses of the corresponding data, could be used to suggest suitable recommendations for furthering soil and water conservation measures.

  Key words: land use/ land cover, vegetation vigour, runoff, soil erosion, remote sensing, GIS