The emerging role of satellite rainfall data in improving the hydro-political situation of flood monitoring in the under-developed regions of the world

The systematic decline of in situ networks for hydrologic measurements has been recognized as a crucial limitation to advancing hydrologic monitoring in medium to large basins, especially those that are already sparsely instrumented. As a collective response, sections of the hydrologic community have recently forged partnerships for the development of space-borne missions for cost-effective, yet global, hydrologic measurements by building upon the technological advancements since the last two decades. In this article, we review the state-of-the-art on flood monitoring in medium and large ungauged basins where satellite remote sensing can facilitate development of a cost-effective mechanism. We present our review in the context of the current hydro-political situation of flood monitoring in flood-prone developing nations situated in international river basins (IRBs). Given the large number of such basins and the difficulty in acquisition of multi-faceted geophysical data, we argue that the conventional data-intensive implementation of physically based hydrologic models that are complex and distributed is time-consuming for global assessment of the utility of proposed global satellite hydrologic missions. A more parsimonious approach is justified at the tolerable expense of accuracy before such missions begin operation. Such a parsimonious approach can subsequently motivate the identified international basins to invest greater effort in conventional and detailed hydrologic studies to design a prototype flood forecasting system in an effort to overcome the hydro-political hurdles to flood monitoring. Through a modeling exercise involving an open-book watershed concept, we demonstrate the value of a parsimonious approach in understanding the utility of NASA-derived satellite rainfall products. It is critical now that real-world operational flood forecasting agencies in the under-developed world come forward to collaborate with the research community in order to leverage satellite rainfall data for greater societal benefit for inhabitants in IRBs.     

Simulation and modeling of rainfall radar measurements for hydrological applications

A procedure is described for the simulation of rainfall radar reflectivity (absolute and differential) measurements by dual linear polarization meteorological radars. The basic requirement that the proposed procedure aims at satisfying is that radar data obtained at the end of the process be correlated in a physically plausible manner to the rainfall field at ground, the latter being generated by means of a stochastic space-time rainfall model. The main goal of the model is to give the possibility to easily check the accuracy of radar rainfall estimates derived by means of procedures and algorithms aimed at minimizing or compensating for the effects of measurement errors associated with several types of meteorological events, with particular reference to requirements of hydrogeological forecast systems. Within the limits imposed by the validity of the adopted model, an analysis was carried out indicating general criteria that may be adopted to achieve a better accuracy in rainfall estimates and a full exploitation of the advantages offered by the radar dual polarization measurement technique.     

Limitations of real-time models for forecasting river flooding from monsoon rainfall

Very intense rainfall during the southwest and northeast monsoons causes severe river flooding in India. Some traditional techniques used for real-time forecasting of flooding involve the relationship between effective rainfall and direct surface runoff, which simplifies the complex interactions between rainfall and runoff processes. There are, however, serious problems in deducing these variables in real time, so it is highly desirable to have a real-time flood forecasting model that would directly relate the observed discharge hydrograph to the observed rainfall. The storage routing model described by Baba and Hoshi (1997), Tanaka et al. (1997), and Baba et al. (2000), and a simplified version of this model, have been used to compute observed river discharge directly from observed hourly rainfall. This method has been used to study rainfall–runoff data of the Ajay River Basin in eastern India. Five intense rainfall events of this basin were studied. Our results showed that the Nash–Sutcliffe efficiency of discharge prediction for these five events was 98.6%, 94.3%, 86.9%, 85.6%, and 67%. The hindcast for the first two events is regarded as completely satisfactory whereas for the next two events it is deemed reasonable and for the fifth it is unsatisfactory. It seems the models will yield accurate hindcast if the rainfall is uniform over the drainage basin. When the rainfall is not uniform the performance of the model is unsatisfactory. In future this problem can, in principle, be corrected by using a weighted amount if rainfall is based upon multiple rain-gauge observations over the drainage basin. This would provide some measure of the dispersion in the rainfall. The model also seems unable to simulate flooding events with multiple peaks.