Towards estimation of extreme floods: examination of the roles of runoff process changes and floodplain flows

This paper presents the development and application of a distributed rainfall-runoff model for extreme flood estimation, and its use to investigate potential changes in runoff processes, including changes to the ‘rating curve’ due to effects of over-bank flows, during the transition from ‘normal’ floods to ‘extreme’ floods. The model has two components: a hillslope runoff generation model based on a configuration of soil moisture stores in parallel and series, and a distributed flood routing model based on non-linear storage-discharge relationships for individual river reaches that includes the effects of floodplain geometries and roughnesses. The hillslope water balance model contains a number of parameters, which are measured or derived a priori from climate, soil and vegetation data or streamflow recession analyses. For reliable estimation of extreme discharges that may extend beyond recorded data, the parameters of the flood routing model are estimated from hydraulic properties, topographic data and vegetation cover of compound channels (main channel and floodplains). This includes the effects of the interactions between the main channel and floodplain sections, which tend to cause a change to the rating curve. The model is applied to the Collie River Basin, 2545 km², in Western Australia and used to estimate the probable maximum flood (PMF) from probable maximum precipitation estimates for this region. When moving from normal floods to the PMFs, application of the model demonstrates that the runoff generation process changes with a substantial increase of saturation excess overland flow through the expansion of saturated areas, and the dominant runoff process in the stream channel changes from in-bank to over-bank flows. The effects of floodplain inundation and floodplain vegetation can significantly reduce the magnitude of the estimated PMFs. This study has highlighted the need for the estimation of a number of critical parameters (e.g. cross-sectional geometry, floodplain vegetation, soil depths) through concerted field measurements or surveys, and targeted laboratory experiments.     

Seasonal Trend in the Occurrence of Nocturnal Drainage Flow on a Forested Slope Under a Tropical Monsoon Climate

Using data for one year, we examined the vertical wind speed profileson a mountain slope covered with forest in northern Thailand undera tropical monsoon climate. We defined two profile patterns: higherwind speeds at greater heights (Pattern 1) and lower wind speeds atgreater heights (Pattern 2). We classified 9.4% of the data as Pattern 2;this pattern tended to occur during the night, at low wind speeds, and with high outgoing longwave radiation. In addition, stable stratification anddecoupling between the canopy surface air and the overlying layers wereobserved when Pattern 2 occurred frequently. These facts suggested thatPattern 2 was caused by a nocturnal drainage flow. The occurrence ofPattern 2 showed a clear seasonal trend, indicating that there is a seasonaltrend in the occurrence of nocturnal drainage flows. Pattern 2 was observedmore frequently between August and February and less frequently betweenMarch and July. This corresponded to the seasonal trend in wind speed, butdid not correspond to the seasonal trend in the outgoing longwave radiation.     

Particulate carbon and nitrogen dynamics in a headwater catchment in Northern Thailand: hysteresis,high yields,and hot spots

Rivers of South and Southeast Asia disgorge large suspended sediment loads, reflecting exceptionally high rates of erosion promoted by natural processes (tectonic and climatic) and anthropogenic (land‐use change) activities that are characteristic of the region. While particulate carbon and nitrogen fluxes have been characterized in some large Asian rivers, less is known about the headwater systems where much sediment and organic material are initially mobilized. This study, conducted in the 74‐km² Mae Sa Experimental Catchment in northern Thailand, shows that the Sa River is an important source for particulate organic carbon (POC) and particulate organic nitrogen (PON) transported to larger river systems and downstream reservoirs. However, the yields during three years of investigation varied greatly: 5.0–22.3 Mg POC km^?2 y^?1 and 0.48–2.02 Mg PON km^?2 y^?1. The 22.3 Mg POC km^?2 y^?1 yield is the highest reported for any river on the Asian continent. Stream samples collected during 12 storms showed that almost 3% of the total suspended solid load is POC 0.7 µm to 2.0 mm in size. This percentage is higher than other values for most large rivers on the continent. Further, we documented a strong pulse hysteretic behaviour in the stream, whereby peak fluxes of POC and PON are often delayed (anticlockwise hysteresis) or accelerated (clockwise hysteresis) relative to stream flow peaks (or are complex), complicating the prediction of storm‐based or annual particulate carbon and nitrogen fluxes. Stream turbidity and total suspended sediment are reasonable proxies for POC and PON concentrations, while stream discharge is not a good predictor variable. Observed C:N ratios for measured particulate samples range from 3 to 83, with the high‐end values likely associated with fresh (non‐decomposed) vegetative material greater than 2 mm in diameter. The C:N ratio (weighted based on three sediment sizes) for 12 events ranges from 7.5 to 15.3. These modest values reflect the relatively low C:N ratios for small size fractions (0.7–0.63 µm) that comprise 50–90% of the TSS load in the events. Overall, organic material <0.63 µm contribute about 75% of the total POC load and 80% of the PON load. The annual C:N ratio for the river is approximately 10–11. Collectively, our findings indicate the occasionally high yields make the Sa River—and potentially other similar headwater rivers—a hot spot for POC and PON transported to downstream water bodies. Complex hysteresis patterns and high year‐to‐year variability hinders our ability to calculate and predict these yields without continuous, automated monitoring of discharge and turbidity. Copyright © 2016 John Wiley & Sons, Ltd.     

Two-dimensional direct current (DC) resistivity inversion: Data space Occam's approach

A data space Occam's inversion algorithm for 2D DC resistivity data has been developed to seek the smoothest structure subject to an appropriate fit to the data. For traditional model space Gauss–Newton (GN) type inversion, the system of equations has the dimensions of M × M, where M is the number of model parameter, resulting in extensive computing time and memory storage. However, the system of equations can be mathematically transformed to the data space, resulting in a dramatic drop in its dimensions to N × N, where N is the number of data parameter, which is usually less than M. The transformation has helped to significantly reduce both computing time and memory storage. Numerical experiments with synthetic data and field data show that applying the data space technique to 2D DC resistivity data for various configurations is robust and accurate when compared with the results from the model space method and the commercial software RES2DINV.     

Throughfall partitioning by trees

Although we know that rainfall interception (the rain caught, stored, and evaporated from aboveground vegetative surfaces and ground litter) is affected by rain and throughfall drop size, what was unknown until now is the relative proportion of each throughfall type (free throughfall, splash throughfall, canopy drip) beneath coniferous and broadleaved trees. Based on a multinational data set of >120 million throughfall drops, we found that the type, number, and volume of throughfall drops are different between coniferous and broadleaved tree species, leaf states, and timing within rain events. Compared with leafed broadleaved trees, conifers had a lower percentage of canopy drip (51% vs. 69% with respect to total throughfall volume) and slightly smaller diameter splash throughfall and canopy drip. Canopy drip from leafless broadleaved trees consisted of fewer and smaller diameter drops (D_{50_DR}, 50th cumulative drop volume percentile for canopy drip, of 2.24 mm) than leafed broadleaved trees (D_{50_DR} of 4.32 mm). Canopy drip was much larger in diameter under woody drip points (D_{50_DR} of 5.92 mm) than leafed broadleaved trees. Based on throughfall volume, the percentage of canopy drip was significantly different between conifers, leafed broadleaved trees, leafless broadleaved trees, and woody surface drip points (p ranged from <0.001 to 0.005). These findings are partly attributable to differences in canopy structure and plant surface characteristics between plant functional types and canopy state (leaf, leafless), among other factors. Hence, our results demonstrating the importance of drop‐size‐dependent partitioning between coniferous and broadleaved tree species could be useful to those requiring more detailed information on throughfall fluxes to the forest floor.     

Reducing hillslope size in digital elevation models at various scales and the effects on slope gradient estimation

Several models simulate watershed areas by delineating hillslopes. Hillslope size depends on the length of stream tributaries, which are affected by the drainage area threshold (DAT). There is no universal approach to identify the appropriate DAT. Therefore, a method to derive the DAT and a series of steps to delineate a watershed into smaller sizes were proposed in this study, and the impact of hillslope size on slope gradient estimation was investigated. The DAT obtained in this study was smaller than that obtained using other methods, resulting in a shorter length of the tributaries. Dividing these tributaries into equal short segments and using them to delineate the study area reduced the size of the hillslope. The results revealed that the shorter the length of the tributaries, the smaller the hillslope size. The accuracy of gradient estimation increased when the size of the hillslope was reduced.