**5. Case study analysis**

*Current Practice in Fluvial Geomorphology - Dynamics and Diversity*

**4. Development in modelling drainage basins**

channel frequency, texture ratio, form factor, circulatory ratio, elongation ratio, relief ratio and length of overland flow. The stream orders and stream number typically provide information on other parameters, suggesting complexity in the parameters [21]. Subsequently, major advancements in remote sensing technology are the availability of many high-quality drainage models or abstraction of reality.

The river basin concept aids the development and management of water resources in many countries, and consequently interests planners and engineers, and scientists, including agriculturists that are interested in the elucidation of hydrological processes. Improvements in water supply and demand enhance hydropower generation, flood control, water supply and irrigation; Recreation, aesthetic ammenities, ecosystem services pollution control are also justifications for scientific interests; especially among hydrologists, soil scientists, geologists, physical geographers and environmental modellers [22]. Concerns about basins probably became noticeable since 300 BC [23, 24], with improved focus on hydraulic infrastructure over flood basins and dams for flood disaster control, intensive agriculture, and industrialisation. Parameterisation of basins for explanatory and predictive modelling purposes later became popular with the thoughts of Horton [25] and Langbein

Digital elevation models (DEMs) are frequently explored for the morphometric

analysis of river basins through the extraction of topographic parameters and stream networks, and their use presents many advantages over traditional topographical maps. DEM is a regular gridded matrix representation of the continuous variation of relief over space [27], and a digital model of the land surface form. The most important requirement of any DEM is that it should have the required accuracy and resolution and be stripped of data voids [28]. Recent increase in the application of DEMs can be attributed to their easy integration within a GIS environment. The Shuttle Radar Topography Mission (SRTM) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) are samples of advanced global DEMs. They have been adopted in a variety of studies where terrain and drainage factors play prominent roles because of convenience of users and open-access availability of the DEMs. The DEM approach is also useful for characterising stream basin because of its easy integration within the GIS environment. It is fast, precise, updated and it is an inexpensive method for drainage basin analysis [29]. The DEM will help to show the general topography of the area and the

In addition, studies have shown that the advantage of timeliness and ability to capture information on larger areas than in studies with traditional surveying methods [21, 30–33] are main strengths of remote sensing and GIS in river basin investigations. GIS is also a viable tool for establishing relationship between drainage morphometry and properties of landforms useful in the development and planning of drainage system. Results from remote sensing and GIS are known to provide decision support information for prioritization of basins, water conservation and natural resource management. Specific results of basin morphometry are also advantageous in the recognition of different terrain parameters and basin's health; measured in terms of runoff and sediment yield index from a basin, flow characteristics and fluvial processes [34, 35]. Malik [30] adopted drainage density and stream frequency to explain control of the runoff pattern, sediment yield and other hydrological parameters within the basin. In addition, Kulkarni [35] argued that dynamism of river morphology is the aftermath of natural processes as well

[26], emphasising concerns on runoff regeneration mechanisms.

**54**

direction of flow of the streams.

#### **5.1 Precipitation input measures**

Main precipitation input into the drainage basin in Nigeria is rainfall based on its location in the tropical region. Whereas the ground-based data has become rather expensive, despite being coarse (almost only available for locations around airports, which are often not representative of the large area that they are meant to represent), satellite-based data sources are poorly explored. This is probably because of the poor awareness and low capacity for remote sensing analysis among many climate experts in the country.

Meanwhile, satellite-based precipitation estimation algorithm use information from two primary sources; the visible and infrared channels from geosynchronous satellites. Many meteorological weather satellites have been launched in the last few decades and some of these satellite rainfall products are freely available in real time on the internet via the web or File Transfer Protocol (FTP). Some of the freely available spatially distributed satellite-based rainfall estimates are the Tropical Rainfall Measuring Mission (TRMM), EUMETSAT's Meteorological Product Extraction Facility (MPEF), and Multi-Sensor Precipitation Estimate-Geostationary (MPEG). Others include the Climate Forecast System Reanalysis (CFSR), the NOAA/Climate Prediction Center Morphing Technique (CMORPH), Climate Research Unit (CRU), and Global Precipitation Climatology Centre (GPCC), European Centre for Medium-Range Weather Forecasting (ERA-Interim), the Naval Research Laboratory's blended product (NRLB) and African Regional Climate (ARC) [41]. These satellites have different spatial and temporal resolutions, thus providing a stream of datasets in support of operational meteorology and many other disciplines. They are scaled to match rain-gauge measurements on land points where ground measurements are available. The TRMM, CRU, GPCC, GPCP, and ERA-INTERIM (Medium-Range Weather Forecasting Reanalysis-Interim) were commonly selected and chosen for use in many studies and have been shown to possess complementary capacity with ground based data based on their high spatial and temporal characteristics, free availability and accessibility online and minimal frequency of missing data. The centre for this is the latest global atmospheric reanalysis (third generation reanalysis) which computes synoptic hourly, daily and monthly means of precipitation by accumulating the available hourly forecast for each calendar month [41]. The ECMWF ERA-Interim reanalysis, provides global precipitation at gridded spatial resolution

of 0.125° × 0.125° (i.e., 13 km). In addition, dataset from the Global Precipitation Climatology Project is made available from October 1996 to present. The GPCP provides daily, global horizontal resolution of 1 × 1° (i.e., 111 km) gridded fields of precipitation. The GPCP 1-DD draws upon several data sources such as GOES, Meteosat, GMS geostationary satellites and with NOAA AVHRR polar-orbiting IR satellite, given the different available input sources (GPCP-1DD v.1.2; [42]). The Tropical Rainfall Measurement Mission (TRMM) satellite, launched in November 1997 is a joint space mission between the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), and the Japan Aerospace Exploration Agency (JAXA). It is a polar orbiting satellite, having a relatively high temporal resolution, designed to monitor rainfall over the global Tropics [43]. The satellite estimates rainfall and energy exchange on tropical and subtropical regions of the world based on the characteristics of cloud cover, cloud tops and temperature.

The great advantage of satellite-based rainfall records is their global coverage, providing information on rainfall frequency and intensity in regions that are in accessible to other observing systems such as rain gauges and radar. Through the aid of satellite weather observing technologies, the influence of viewing and understanding tropical rainfall systems has been greatly improved. In recent studies, several satellite-based rainfall products have been subjected to cross-validation tests over many regions to ascertain the accuracy of their rainfall estimations. The performance of satellite precipitation estimates over land areas has been reported to be highly dependent on the rainfall regime and the temporal and spatial scale of the retrievals [44].
