Fuzzy Logic for Rainfall-Runoff Modelling Considering Soil Moisture

Abstract

This study developed Mamdani-type fuzzy logic model to simulate daily discharge as a function of soil moisture measured at three different depths (10, 20 and 40 cm) and rainfall. The model was applied to 13 km 2 size Colorso Basin in central Italy for a period from October 2002 to April 2004. For each variable of soil moisture, rainfall, and discharge, 9 fuzzy subsets were employed while 30 fuzzy rules, relating the input variables (soil moisture and rainfall) to the output variable (discharge), were optimized. The model employed the min inferencing, max composition, and the centroid method. The model application results revealed that Mamdani-type fuzzy logic model can be employed to incorporate soil moisture along with rainfall to simulate discharge. Using soil moisture measured at 40 cm soil depth along with rainfall produced better simulation of discharge with NS=0.68 and R= 0.82. The performance of the model was also tested against a conceptual rainfallrunoff model of MISDc (Modello Idrologico Semi-Distribuito in continuo). MISDc couples an event-specific component with a module for continuous time soil water balance for taking into account the variable antecedent wetness conditions. The MISDc model requires estimation of seven parameters and the measurements of the hydrometeorological variables such as rainfall and air temperature. The comparative study revealed that fuzzy model performs better in capturing runoff peak rates and overall trend of high and small flooding events.

Evaluating Consistency between the Remotely Sensed Soil Moisture and the Hydrological Model-Simulated Soil Moisture in the Qujiang Catchment of China

“…The Qujiang catchment, located between 106 • 00 E-109 • 00 E and 30 • 00 N-33 • 00 N, is a typical humid catchment in southwestern China [35] with a drainage area of 39211 km 2 (Figure 1). It originates at Tiechuan Mountain situated at the juncture of the Shanxi and Sichuan Provinces of China and flows southwest to the Jialing River at the north of Chongqing.…”

“…The direct field measurements of soil moisture are thought to be fairly accurate, but are costly, with small coverage areas, and only provide point-based measurements rather than areal values, which are of more interest for practical applications. Indirect acquisition ways, including remote sensing (optical, thermal infrared and microwave) and hydrological models (either the physically-based land-surface models, or rainfall-runoff hydrological models), offer the possibility to provide the areal soil moisture information on a low-cost basis, but with less accuracy than ground point measurements [2,3].…”

Implementation of Univariate Paradigm for Streamflow Simulation Using Hybrid Data-Driven Model: Case Study in Tropical Region

“…The learning rates and the number of memory taps also significantly impact the performance of ANN model. Besides ANN, the fuzzy logic (FL) which uses the concept of uncertainty is another SC-based technique that has been received much attention for modeling hydrological phenomena in last three decades [18], [19]. Similar to ANN, the FL has several shortcomings such as decision on suitable variables.…”

Runoff estimation using modified adaptive neuro-fuzzy inference system

“…Numerous evidences are available in the literature where fuzzy logic (FL) based systems excelled in modeling various hydrological events such as rainfall, runoff, streamflow, etc. [2][3][4][5]. The presence of uncertainties and imprecision in these domains make FL based systems a suitable candidate for modeling purpose.…”