Application Of Geographic Information System And Hydrological Modelling Of Sungai Galas, Kelantan, Malaysia

Flooding is one of the natural hazard in the world as well as in Malaysia. Kelantan is also effected by flooding which need to be analysed. Flood analysis can be done through hydrological modelling by using high resolution data to find exact causes and effects of flooding. But in the absence high resolution or in situ data, what are the alternatives to conduct hydrological modelling? The objectives of this study were (i) to develop alternative methodologies and models for the generation of accurate flooding parameter’s values by using remote sensing and Geographic Information System (GIS) in a data sparse environment in Kelantan

One- and Two-Dimensional Hydrological Modelling and Their Uncertainties

Earth processes, which occur in land, air and ocean in different environment and at different scales, are very complex. Flooding is also a part of the complex processes, which need to be assessed accurately to know the accurate spatial and temporal changes of flooding and their causes. Hydrological modelling has been used by several researchers in river and floodplain modelling for flood analysis. In this chapter, factors affecting flash flood, possible options of basic input parameters in one- and two-dimensional hydrological models in data sparse environment, some case studies and uncertainty in hydrological modelling were discussed. This discussion will help the readers to understand the flooding factors, selection of input parameters in data sparse environment, a brief insight of one- and two-dimensional hydrological models and uncertainties in their input and model parameters and model structures

Characteristics and Assessment of Groundwater

Groundwater system is very vital to humanity and the ecosystem. Aquifers are determined based on the absence or presence of water table positioning, that is, confined, unconfined, leaky aquifers and fractured aquifers. The objective of this chapter is to discuss the characteristic and assessment of groundwater within the scope of vertical distribution of GW, types of the aquifer system, types of SW-GW interface, and SW-GW interaction at both local and regional scales. The properties of the aquifer depend on the physical characteristics of the materials (porosity, permeability, specific yield, specific storage, and hydraulic conductivities) which are determined by techniques like resistivity surveys and pumping tests followed by remote sensing and geographic information system for better information on the groundwater system. Furthermore, understanding the SW-GW interactions through available methods (seepage meter, heat tracer, and environmental tracer) is useful in watershed management, that is, risk management and assessment of the aquifer system

Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate

Complex topography and wind characteristics play important roles in rising air masses and in daily spatial distribution of the precipitations in complex region. As a result, its spatial discontinuity and behaviour in complex areas can affect the spatial distribution of precipitation. In this work, a two-fold concept was used to consider both spatial discontinuity and topographic and wind speed in average daily spatial precipitation estimation using Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR) in tropical climates. First, wet and dry days were identified by the two methods. Then the two models based on MLR (Model 1 and Model 2) were applied on wet days to estimate the precipitation using selected predictor variables. The models were applied for month wise, season wise and year wise daily averages separately during the study period. The study reveals that, Model 1 has been found to be the best in terms of categorical statistics, R2 values, bias and special distribution patterns. However, it was found that sets of different predictor variables dominates in different months, seasons and years. Furthermore, necessities of other data for further enhancement of the results were suggested

Morphometric analysis of song watershed: A GIS approach

The present study conducted in Dehradun district of Uttarakhand state advocates that remotely sensed data and GIS based approach in evaluation of drainage morphometric parameter was more appropriate than the conventional methods. Various linear, aerial and relief aspects were taken into consideration to analyze the morphometry of the study area and digital elevation model (DEM) and slope map of the catchment area were generated from ASTER data of 30 m resolution. The drainage patterns were mainly dendritic to sub dendritic. The slope of the study area had been divided into five equal intervals viz. gentle (00 to 130), moderate (140 to 260), moderately steep (270 to 390), steep (400 to 520), and very steep (530 to 650). The order of stream of the study area ranged from 1st order to 6th order. The variation in stream length ratio might be due to difference in slope and topographic conditions. The variation of bifurcation ratio in the catchment area was ascribed to the difference in topography and geometric development. The drainage density was 2.03 km2 which was moderate. The drainage texture was 8.75 which shows that the lithology is not so complex. © 2019 Ecological Society of India. All rights reserved

Crop Acreage and Crop Yield Estimation using Remote Sensing and GIS Techniques, Bulandshahr District

Present study was conducted in the Bulandshahr district, Uttar Pradesh, India, for land use land cover changes, density of vegetation, difference vegetation index and estimation of crop yield for the year of 2000 and 2014. Remote sensing and geographical information system techniques were used in this study. Five land use land cover classes were identified such as built-up land, open land, crop land, and natural vegetation and water bodies through supervised classification with an accuracy of 97.9 and 99.5 per cent for the year 2000 and 2014, respectively. Increment in built-up land, open land and crop land were observed while natural vegetation was decline up to 15.6 per cent in fourteen years. Highest NDVI values for 2000 and 2014 were 0.4141 and 0.4166 while lowest were -0.4127 and -0.4166. In the crop yield estimation, an average of 3.7 x 106 ton ha-1 crop production was estimated. Overall, the study showed that the use of remote sensing and GIS in crop yield estimation was better as compared to traditional techniques. © 2019 Ecological Society of India. All rights reserved

Upscaling of Surface Water and Groundwater Interactions in Hyporheic Zone from Local to Regional Scale

The groundwater (GW) and surface water (SW) interaction (SW-GW) through the hyporheic zone is a significant component in sustainable water resource management. The complexities in SW-GW interactions increase from a local to a regional scale and are affected by variation in hydraulic, hydrologic, and hydrogeologic (3H) processes. Controlling factors and their upscaling of these processes to assess SW-GW interaction have not been addressed sufficiently in previous studies. Additionally, it is unclear what the effective factors are at different scales during the upscaling. Therefore, the present review focused on controlling factors of 3H processes in SW-GW interaction and their upscaling techniques. Relevancy of controlling factors was identified at different scales. Applications of different approaches and their uncertainties were also discussed for the characterization of SW-GW interactions. The study revealed that the improved data from different approaches is crucial for machine learning training and its application in the SW and GW assessment at local, sub-catchment, and catchment scales. Based on the outcomes, a framework has been proposed to execute modalities of controlling factors using remote sensing, geophysics, and artificial intelligence. The proposed framework could help in handling big data and accurate upscaling for water resource management

Upscaling of Surface Water and Groundwater Interactions in Hyporheic Zone from Local to Regional Scale

The groundwater (GW) and surface water (SW) interaction (SW-GW) through the hyporheic zone is a significant component in sustainable water resource management. The complexities in SW-GW interactions increase from a local to a regional scale and are affected by variation in hydraulic, hydrologic, and hydrogeologic (3H) processes. Controlling factors and their upscaling of these processes to assess SW-GW interaction have not been addressed sufficiently in previous studies. Additionally, it is unclear what the effective factors are at different scales during the upscaling. Therefore, the present review focused on controlling factors of 3H processes in SW-GW interaction and their upscaling techniques. Relevancy of controlling factors was identified at different scales. Applications of different approaches and their uncertainties were also discussed for the characterization of SW-GW interactions. The study revealed that the improved data from different approaches is crucial for machine learning training and its application in the SW and GW assessment at local, sub-catchment, and catchment scales. Based on the outcomes, a framework has been proposed to execute modalities of controlling factors using remote sensing, geophysics, and artificial intelligence. The proposed framework could help in handling big data and accurate upscaling for water resource management