A remote sensing contribution to hydrologic modelling in arid and inaccessible watersheds,Pishin Lora basin,Pakistan

The lack of adequate field measurements often hampers the construction and calibration of rainfall‐runoff models over many of the world's watersheds. We adopted methodologies that rely heavily on readily available remote sensing datasets as viable alternatives for assessing, managing, and modelling of such remote and inadequately gauged regions. The Soil and Water Assessment Tool was selected for continuous (1998–2005) rainfall‐runoff modelling of one such area, the northeast part of the Pishin Lora basin (NEPL). Input to the model included satellite‐based Tropical Rainfall Measuring Mission precipitation data, and modelled runoff was calibrated against satellite‐based observations, the latter included: (i) monthly estimates of the water volumes impounded by the Khushdil Khan (latitude 30°40′N, longitude 67°40′E), and the Kara Lora (latitude 30°34′N, longitude 66°52′E) reservoirs, and (ii) inferred wet versus dry conditions in streams across the NEPL. Calibrations were also conducted against observed flow reported from the Burj Aziz Khan station at the NEPL outlet (latitude 30°20′N; longitude 66°35′E). Model simulations indicate that (i) average annual precipitation (1998–2005), runoff and recharge in the NEPL are 1300 × 10⁶ m³, 148 × 10⁶ m³, and 361 × 10⁶ m³, respectively; (ii) within the NEPL watershed, precipitation and runoff are high for the northeast (precipitation: 194 mm/year; runoff: 38 × 10⁶ m³/year) and northwest (134 mm/year; 26 × 10⁶ m³/year) basins compared to the southern basin (124 mm/year; 8 × 10⁶ m³/year); and (3) construction of delay action dams in the northeast and northwest basins could increase recharge from 361 × 10⁶ m³/year up to 432 × 10⁶ m³/year and achieve sustainable extraction. The adopted methodologies are not a substitute for traditional approaches, but they could provide first‐order estimates for rainfall, runoff, and recharge in the arid and semi‐arid parts of the world that are inaccessible and/or lack adequate coverage with field data. Copyright © 2011 John Wiley & Sons, Ltd.     

Modeling the Impact of Stream Discharge Events on Riparian Solute Dynamics

The biogeochemical composition of stream water and the surrounding riparian water is mainly defined by the exchange of water and solutes between the stream and the riparian zone. Short-term fluctuations in near stream hydraulic head gradients (e.g., during stream flow events) can significantly influence the extent and rate of exchange processes. In this study, we simulate exchanges between streams and their riparian zone driven by stream stage fluctuations during single stream discharge events of varying peak height and duration. Simulated results show that strong stream flow events can trigger solute mobilization in riparian soils and subsequent export to the stream. The timing and amount of solute export is linked to the shape of the discharge event. Higher peaks and increased durations significantly enhance solute export, however, peak height is found to be the dominant control for overall mass export. Mobilized solutes are transported to the stream in two stages (1) by return flow of stream water that was stored in the riparian zone during the event and (2) by vertical movement to the groundwater under gravity drainage from the unsaturated parts of the riparian zone, which lasts for significantly longer time (> 400 days) resulting in long tailing of bank outflows and solute mass outfluxes. We conclude that strong stream discharge events can mobilize and transport solutes from near stream riparian soils into the stream. The impact of short-term stream discharge variations on solute exchange may last for long times after the flow event.     

A wavelet based approach for combining the outputs of different rainfall–runoff models

The rainfall–runoff modelling being a stochastic process in nature is dependent on various climatological variables and catchment characteristics and therefore numerous hydrological models have been developed to simulate this complex process. One approach to modelling this complex non-linear rainfall–runoff process is to combine the outputs of various models to get more accurate and reliable results. This multi-model combination approach relies on the fact that various models capture different features of the data, and hence combination of these features would yield better result. This study for the first time presented a novel wavelet based combination approach for estimating combined runoff The simulated daily output (Runoff) of five selected conventional rainfall–runoff models from seven different catchments located in different parts of the world was used in current study for estimating combined runoff for each time period. Five selected rainfall–runoff models used in this study included four data driven models, namely, the simple linear model, the linear perturbation model, the linearly varying variable gain factor model, the constrained linear systems with a single threshold and one conceptual model, namely, the soil moisture accounting and routing model. The multilayer perceptron neural network method was used to develop combined wavelet coupled models to evaluate the effect of wavelet transformation (WT). The performance of the developed wavelet coupled combination models was compared with their counterpart simple combination models developed without WT. It was concluded that the presented wavelet coupled combination approach outperformed the existing approaches of combining different models without applying input WT. The study also recommended that different models in a combination approach should be selected on the basis of their individual performance.     

Mechanical response of saturated and unsaturated gravels of different sizes in drained triaxial testing

Acta Geotechnica - During the construction of pavements, gravelly soil is used as the main material in the base and sub-base layers. Predicting the deformation behaviour of gravelly soil has been...     

Assessment of drought hazard impact on wheat cultivation using standardized precipitation index in Iran

The assessment of drought hazard impacts on wheat cultivation as a strategic crop in Iran is essential for making mitigation plans to reduce the impact of drought. Standardized precipitation index has gained importance in recent years as a potential drought indicator and is being used more frequently for assessment of drought hazard in many countries. In the present study, the calculated standardized precipitation index for 48 stations dataset in the 30-year time scale fulfilled 30 statistical matrices. The drought hazard index map was produced by sum overlaying the spatial representations of 30 statistical matrices and categorized into four levels of low, moderate, high, and very high, which demonstrated probability of drought occurrences of 10–20 %, 20–30 %, 30–40 %, and 40–50 %, respectively. Finally, after the general division of zonal statistics in drought hazard index map of Iran, major drought hazard zones were geographically classified into five zones. The statistical analysis showed a significant correlation (R ²?=?0.701 to 0.648) between drought occurrences and wheat cultivation including surface area and total production for these drought hazard zones.