Sub-daily simulation of mountain flood processes based on the modified soil water assessment tool (SWAT) model

Floods not only provide a large amount of water resources, but they also cause serious disasters. Although there have been numerous hydrological studies on flood processes, most of these investigations were based on rainfall-type floods in plain areas. Few studies have examined high temporal resolution snowmelt floods in high-altitude mountainous areas. The Soil Water Assessment Tool (SWAT) model is a typical semi-distributed, hydrological model widely used in runoff and water quality simulations. The degree-day factor method used in SWAT utilizes only the average daily temperature as the criterion of snow melting and ignores the influence of accumulated temperature. Therefore, the influence of accumulated temperature on snowmelt was added by increasing the discriminating conditions of rain and snow, making that more suitable for the simulation of snowmelt processes in high-altitude mountainous areas. On the basis of the daily scale, the simulation of the flood process was modeled on an hourly scale. This research compared the results before and after the modification and revealed that the peak error decreased by 77% and the time error was reduced from +/- 11 h to +/- 1 h. This study provides an important reference for flood simulation and forecasting in mountainous areas

Using NWP Analysis in Satellite Rainfall Estimation of Heavy Precipitation Events over Complex Terrain

This study investigates the use of Weather Research and Forecasting (WRF) high-resolution storm analysis in satellite rainfall estimation over complex terrains. Rainfall estimation here is based on the NOAA-Climate Prediction Center morphing (CMORPH) product. Specifically, CMORPH rainfall is adjusted by applying a power-law function whose parameter values are obtained from the comparison between WRF and CMORPH hourly rain rates. Results are presented based on the analyses of five storm cases that induced catastrophic floods in southern Europe. The WRF-based adjusted CMORPH rain rates exhibited improved error statistics against independent radar-rainfall estimates. We show that the adjustment reduces the underestimation of high rain rates thus moderating the strong rainfall magnitude dependence of CMORPH bias. The higher Heidke skill scores for all rain rate thresholds indicate that the adjustment procedure meliorates CMORPH rain rates to provide a better estimation. Results also indicate that the missed rain detection of CMORPH rainfall estimates are also identifiable in the WRF-CMORPH comparison, however, the herein adjustment procedure does not incorporate this effect on CMORPH estimates

Uncertainties in the Hydrological Modelling Using Remote Sensing Data over the Himalayan Region

Himalayas the “roof of the world” are the source of water supply for major South Asian Rivers and fulfill the demand of almost one sixth of world’s humanity. Hydrological modeling poses a big challenge for Himalayan River Basins due to complex topography, climatology and lack of quality input data. In this study, hydrological uncertainties arising due to remotely sensed inputs, input resolution and model structure has been highlighted for a Himalayan Gandak River Basin. Firstly, spatial input DEM (Digital Elevation Model) from two sources SRTM (Shuttle Radar Topography Mission) and ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer) with resolutions 30m, 90m and 30m respectively has been evaluated for their delineation accuracy. The result reveals that SRTM 90m has best performance in terms of least area delineation error (13239.28 km2) and least stream network delineation error. The daily satellite precipitation estimates TRMM 3B42 V7 (Tropical Rainfall Monitoring Mission) and CMORPH (Climate Prediction Center MORPHing Technique) are evaluated for their feasibly over these terrains. Evaluation based on various scores related to visual verification method, Yes/no dichotomous, and continuous variable verification method reveal that TRMM 3B42 V7 has better scores than CMORPH. The effect of DEM resolution on the SWAT (Soil Water Assessment Tool) model outputs has been demonstrated using sixteen DEM grid sizes (40m-1000m). The analysis reveals that sediment and flow are greatly affected by the DEM resolutions (for DEMs>300m). The amount of total nitrogen (TN) and total phosphorous (TP) are found affected via slope and volume of flow for DEM grid size ≥150m. The T-test results are significant for SWAT outputs for grid size >500m at a yearly time step. The SWAT model is accessed for uncertainty during various hydrological processes modeling with different setups/structure. The results reflects that the use of elevation band modeling routine (with six to eight elevation bands) improves the streamflow statistics and water budgets from upstream to downstream gauging sites. Also, the SWAT model represents a consistent pattern of spatiotemporal snow cover dynamics when compared with MODIS data. At the end, the uncertainty in the stream flow simulation for TRMM 3B42 V7 for various rainfall intensity has been accessed with the statistics Percentage Bias (PBIAS) and RSR (RMSE-observations Standard Deviation Ratio). The results found that TRMM simulated streamflow is suitable for moderate (7.5 to 35.4 mm/day) to heavy rainfall intensities (35.5 to 124.4 mm/day). The finding of the present work can be useful for TRMM based studies for water resources management over the similar parts of the world

Moist Orographic Convection: Physical Mechanisms and Links to Surface-Exchange Processes

This paper reviews the current understanding of moist orographic convection and its regulation by surface-exchange processes. Such convection tends to develop when and where moist instability coincides with sufficient terrain-induced ascent to locally overcome convective inhibition. The terrain-induced ascent can be owing to mechanical (airflow over or around an obstacle) and/or thermal (differential heating over sloping terrain) forcing. For the former, the location of convective initiation depends on the dynamical flow regime. In “unblocked” flows that ascend the barrier, the convection tends to initiate over the windward slopes, while in “blocked” flows that detour around the barrier, the convection tends to initiate upstream and/or downstream of the high terrain where impinging flows split and rejoin, respectively. Processes that destabilize the upstream flow for mechanically forced moist convection include large-scale moistening and ascent, positive surface sensible and latent heat fluxes, and differential advection in baroclinic zones. For thermally forced flows, convective initiation is driven by thermally direct circulations with sharp updrafts over or downwind of the mountain crest (daytime) or foot (nighttime). Along with the larger-scale background flow, local evapotranspiration and transport of moisture, as well as thermodynamic heterogeneities over the complex terrain, regulate moist instability in such events. Longstanding limitations in the quantitative understanding of related processes, including both convective preconditioning and initiation, must be overcome to improve the prediction of this convection, and its collective effects, in weather and climate models. View Full-Tex

Distributed vs. semi-distributed simulations of snowpack dynamics in alpine areas: case study in the upper Arve catchment, French Alps, 1989–2015

We evaluated distributed and semi-distributed modeling approaches to simulating the spatial and temporal evolution of snow and ice over an extended mountain catchment, using the Crocus snowpack model. The distributed approach simulated the snowpack dynamics on a 250-m grid, enabling inclusion of terrain shadowing effects. The semi-distributed approach simulated the snowpack dynamics for discrete topographic classes characterized by elevation range, aspect, and slope. This provided a categorical simulation that was subsequently spatially re-projected over the 250-m grid used for the distributed simulations. The study area (the upper Arve catchment, western Alps, France) is characterized by complex topography, including steep slopes, an extensive glaciated area, and snow cover throughout the year. Simulations were carried out for the period 1989–2015 using the SAFRAN meteorological forcing system. The simulations were compared using four observation datasets including point snow depth measurements, seasonal and annual glacier surface mass balance, snow covered area evolution based on optical satellite sensors, and the annual equilibrium-line altitude of glacier zones, derived from satellite images. The results showed that in both approaches the Crocus snowpack model effectively reproduced the snowpack distribution over the study period. Slightly better results were obtained using the distributed approach because it included the effects of shadows and terrain characteristics

Uncertainty in hydrological estimation

2021 Spring.Includes bibliographical references.Detailed hydrometeorologic analyses and uncertainty assessments are needed to aid water resources decision-making, to account for upstream-downstream linkages and dominant process scale for integrated land and water resources management and planning. The water balance is a fundamental concept in hydrology that inspires many tools for predicting the specific components including precipitation, streamflow, soil moisture, and groundwater storage. A water balance is typically expressed as an equation that relates water inputs, outputs, and storage of a system. The water balance model is applied to analyze the allocation of water among components of the hydrologic system. Knowledge on the components composing inputs and outputs in a water balance are essential to understanding watershed processes. While methods to measure and model water balance components continue to improve, all components of the balance have substantial uncertainty. Methods to analyze a water balance should acknowledge these uncertainties and consider how they propagate through water balance calculations in order to better assist water resources decisions. This research investigated four water balance components: (1) snowpack sublimation, (2) precipitation as snow, (3) precipitation as rain, and (4) stream discharge in mountainous watersheds in order to examine and build our knowledge of uncertainty in the water balance for mountainous environments. The research presented in this dissertation supports a theme that hydrology is a highly uncertain science, where uncertainty is a result of the hydrologic community's knowledge gap to accurately model physics of atmospheric and hydrologic processes. A finding of this work is that no component of the water balance can be quantified at watershed scale without estimating he associated uncertainty. Results highlight that mean cumulative snowpack sublimation uncertainty is 41% with individual input variable uncertainties in the range of 1 to 29%; simulated to observed basin mean snow depth was estimated within 15% for 10-years while extreme dry and wet years were within 5%; and forcing precipitation datasets used in hydrologic models to estimate streamflow have cumulative uncertainties in the range of 30 to 60%. Results of this dissertation identify the importance to account for uncertainty in water resources, i.e., Monte Carlo methods, to properly account for and quantify associated risks in water management and design infrastructure decisions

The impact of initial conditions on convection-permitting simulations of a flood event over complex mountainous terrain

Abstract. Western Norway suffered major flooding after 4 d of intense rainfall during the last week of October 2014. While events like this are expected to become more frequent and severe under a warming climate, convection-permitting scale models are showing their skill with respect to capturing their dynamics. Nevertheless, several sources of uncertainty need to be taken into account, including the impact of initial conditions on the precipitation pattern and discharge, especially over complex, mountainous terrain. In this paper, the Weather Research and Forecasting Model Hydrological modelling system (WRF-Hydro) is applied at a convection-permitting scale, and its performance is assessed in western Norway for the aforementioned flood event. The model is calibrated and evaluated using observations and benchmarks obtained from the Hydrologiska Byråns Vattenbalansavdelning (HBV) model. The calibrated WRF-Hydro model performs better than the simpler conceptual HBV model, especially in areas with complex terrain and poor observational coverage. The sensitivity of the precipitation pattern and discharge to poorly constrained elements such as spin-up time and snow conditions is then examined. The results show the following: (1) the convection-permitting WRF-Hydro simulation generally captures the precipitation pattern/amount, the peak flow volume and the timing of the flood event; (2) precipitation is not overly sensitive to spin-up time, whereas discharge is slightly more sensitive due to the influence of soil moisture, especially during the pre-peak phase; and (3) the idealized snow depth experiments show that a maximum of 0.5 m of snow is converted to runoff irrespective of the initial snow depth and that this snowmelt contributes to discharge mostly during the rainy and the peak flow periods. Although further targeted experiments are needed, this study suggests that snow cover intensifies the extreme discharge instead of acting as a sponge, which implies that future rain-on-snow events may contribute to a higher flood risk