Hydrologic responses to land cover change: the case of Jedeb mesoscale catchment,Abay/Upper Blue Nile basin,Ethiopia

The objective of this study was to quantify the impacts of land use/land cover (LULC) change on the hydrology of the Jedeb, an agricultural dominated mesoscale catchment, in the Abay/Upper Blue Nile basin, Ethiopia. Two methods have been used. First, the trends of certain daily flow variability parameters were evaluated to detect statistical significance of the change of the hydrologic response. Second, a conceptual monthly hydrological model was used to detect changes in the model parameters over different periods to infer LULC change. The results from the statistical analysis of the daily flows between 1973 and 2010 reveal a significant change in the response of the catchment. Peak flow is enhanced, i.e. response appears to be flashier. There is a significant increase in the rise and fall rates of the flow hydrograph, as well as the number of low‐flow pulses below a threshold level. The discharge pulses show a declining duration with time. The model result depicts a change in model parameters over different periods, which could be attributed to an LULC change. The model parameters representing soil moisture conditions indicated a gradual decreasing trend, implying limited storage capacity likely attributed to increasing agricultural farming practices in the catchment. This resulted in more surface runoff and less infiltration into the soil layers. The results of the monthly flow duration curve analysis indicated large changes of the flow regime. The high flow has increased by 45% between the 1990s and 2000s, whereas the reduction in low flows was larger: a 15% decrease between 1970s and 1980s, 39% between 1980s and 1990s and up to 71% between 1990s and 2000s. These results, could guide informed catchment management practices to reduce surface runoff and augment soil moisture level in the Jedeb catchment. Copyright © 2013 John Wiley & Sons, Ltd.     

Response of soil aggregate disintegration to the different content of organic carbon and its fractions during splash erosion

Aggregate disintegration is a critical process in soil splash erosion. However, the effect of soil organic carbon (SOC) and its fractions on soil aggregates disintegration is still not clear. In this study, five soils with similar clay contents and different contents of SOC have been used. The effects of slaking and mechanical striking on splash erosion were distinguished by using deionized water and 95% ethanol as raindrops. The simulated rainfall experiments were carried out in four heights (0.5, 1.0, 1.5 and 2.0 m). The result indicated that the soil aggregate stability increased with the increases of SOC and light fraction organic carbon (LFOC). The relative slaking and the mechanical striking index increased with the decreases of SOC and LFOC. The reduction of macroaggregates in eroded soil gradually decreased with the increase of SOC and LFOC, especially in alcohol test. The amount of macroaggregates (>0.25 mm) in deionized water tests were significantly less than that in alcohol tests under the same rainfall heights. The contribution of slaking to splash erosion increased with the decrease of heavy fractions organic carbon. The contribution of mechanical striking was dominant when the rainfall kinetic energy increased to a range of threshold between 9 J m⁻² mm⁻¹ and 12 m⁻² mm⁻¹. This study could provide the scientific basis for deeply understanding the mechanism of soil aggregates disintegration and splash erosion.     

Calibration of paired watersheds: Utility of moving sums in presence of externalities

Historically, paired watershed studies have been used to quantify the hydrological effects of land use and management practices by concurrently monitoring 2 similar watersheds during calibration (pretreatment) and post‐treatment periods. This study characterizes seasonal water table and flow response to rainfall during the calibration period and tests a change detection technique of moving sums of recursive residuals (MOSUM) to select calibration periods for each control–treatment watershed pair when the regression coefficients for daily water table elevation were most stable to minimize regression model uncertainty. The control and treatment watersheds were 1 watershed of 3–4‐year‐old intensely managed loblolly pine (Pinus taeda L.) with natural understory, 1 watershed of 3–4‐year‐old loblolly pine intercropped with switchgrass (Panicum virgatum), 1 watershed of 14–15‐year‐old thinned loblolly pine with natural understory (control), and 1 watershed of switchgrass only. The study period spanned from 2009 to 2012. Silvicultural operational practices during this period acted as external factors, potentially shifting hydrologic calibration relationships between control and treatment watersheds. MOSUM results indicated significant changes in regression parameters due to silvicultural operations and were used to identify stable relationships for water table elevation. None of the calibration relationships developed using this method were significantly different from the classical calibration relationship based on published historical data. We attribute that to the similarity of historical and 2010–2012 leaf area index on control and treatment watersheds as moderated by the emergent vegetation. Although the MOSUM approach does not eliminate the need for true calibration data or replace the classic paired watershed approach, our results show that it may be an effective alternative approach when true data are unavailable, as it minimizes the impacts of external disturbances other than the treatment of interest.     

The data‐driven approach as an operational real‐time flood forecasting model

Accurate water level forecasts are essential for flood warning. This study adopts a data‐driven approach based on the adaptive network–based fuzzy inference system (ANFIS) to forecast the daily water levels of the Lower Mekong River at Pakse, Lao People's Democratic Republic. ANFIS is a hybrid system combining fuzzy inference system and artificial neural networks. Five ANFIS models were developed to provide water level forecasts from 1 to 5 days ahead, respectively. The results show that although ANFIS forecasts of water levels up to three lead days satisfied the benchmark, four‐ and five‐lead‐day forecasts were only slightly better in performance compared with the currently adopted operational model. This limitation is imposed by the auto‐ and cross‐correlations of the water level time series. Output updating procedures based on the autoregressive (AR) and recursive AR (RAR) models were used to enhance ANFIS model outputs. The RAR model performed better than the AR model. In addition, a partial recursive procedure that reduced the number of recursive steps when applying the AR or the RAR model for multi‐step‐ahead error prediction was superior to the fully recursive procedure. The RAR‐based partial recursive updating procedure significantly improved three‐, four‐ and five‐lead‐day forecasts. Our study further shows that for long lead times, ANFIS model errors are dominated by lag time errors. Although the ANFIS model with the RAR‐based partial recursive updating procedure provided the best results, this method was able to reduce the lag time errors significantly for the falling limbs only. Improvements for the rising limbs were modest. Copyright © 2011 John Wiley & Sons, Ltd.     

Remote sensing and information value (IV) model for regional mapping of fluvial channels and topographic wetness in the Saudi Arabia

This study aims to map regions of near surface fluvial channels, mega-basins and topographic wetness in Saudi Arabia using remote sensing data and an information value (IV) model, which is a modified approach of weight of evidence. We used the new version of the Shuttle Radar Topographic Mission (SRTM) to delineate the fluvial channels, mega-basin, and slope. These hydrological parameters were used to index the topographic wetness of each mega-basin in the region based on IV in a Geographic Information System. We validated our method using the Space Imaging Radar-C and Landsat 8 images and compared the textural features (fluvial channels) evident from SRTM digital elevation model and to determine whether these patterns were different. Our results revealed that the region is drained by nine tributaries and that the Err Rub Al Khali and Sahba mega-basins have the highest value of the IV and topographic wetness values; the Arran and coastal mega-basins have the lowest value of the IV and topographic wetness values. An integrated approach is timely and economically effective and can be applied throughout the arid and semi-arid regions to help hydrologists and urban developers.     

The application of remote sensing data to diagnose soil degradation in the Dakhla depression – Western Desert,Egypt

Dakhla depression in Egypt’s Western Desert is experiencing two soil degradation processes, notably: soil salinization and sand encroachment. The present study aimed to diagnose the severity of these processes using remote sensing. Soil salinity was determined by spectral regression analysis between tasselled cap spectral transform extracted from a Landsat-8 image acquired in September 2013 along with synchronized soil salinity measurements. Assessment of sand advance rate was conducted by temporal change detection of brilliant crescentic sand dune visualized by Google Earth in old (2002) and recent (2013) images. Results showed that salinized soils (dS/m4<) represent 91% of bare lands and salinization is attributed to aridity, topography and poor drainage. Barchan dunes north and south of Abu Tartur escarpment moved at rates of 5.9 and 3.6 m/year, respectively. The escarpment protected the majority of the depression from massive dune invasion. However, sand encroachment is clearly observed west of the depression.     

A hydrochemical study of the Hammam Righa geothermal waters in north-central Algeria

This study focuses on the hydrochemical characteristics of 47 water samples collected from thermal and cold springs that emerge from the Hammam Righa geothermal field, located in north-central Algeria. The aquifer that feeds these springs is mainly situated in the deeply fractured Jurassic limestone and dolomite of the Zaccar Mount. Measured discharge temperatures of the cold waters range from 16.0 to 26.5 °C and the hot waters from 32.1 to 68.2 °C. All waters exhibited a near-neutral pH of 6.0–7.6. The thermal waters had a high total dissolved solids (TDS) content of up to 2527 mg/l, while the TDS for cold waters was 659.0–852.0 mg/l. Chemical analyses suggest that two main types of water exist: hot waters in the upflow area of the Ca–Na–SO₄ type (Hammam Righa) and cold waters in the recharge zone of the Ca–Na–HCO₃ type (Zaccar Mount). Reservoir temperatures were estimated using silica geothermometers and fluid/mineral equilibria at 78, 92, and 95 °C for HR4, HR2, and HR1, respectively. Stable isotopic analyses of the δ¹⁸O and δD composition of the waters suggest that the thermal waters of Hammam Righa are of meteoric origin. We conclude that meteoric recharge infiltrates through the fractured dolomitic limestones of the Zaccar Mount and is conductively heated at a depth of 2.1–2.2 km. The hot waters then interact at depth with Triassic evaporites located in the hydrothermal conduit (fault), giving rise to the Ca–Na–SO₄ water type. As they ascend to the surface, the thermal waters mix with shallower Mg-rich groundwater, resulting in waters that plot in the immature water field in the Na–K–Mg diagram. The mixing trend between cold groundwaters from the recharge zone area (Zaccar Mount) and hot waters in the upflow area (Hammam Righa) is apparent via a chloride-enthalpy diagram that shows a mixing ratio of 22.6 < R < 29.2 %. We summarize these results with a geothermal conceptual model of the Hammam Righa geothermal field.     

Assessing groundwater storage changes in the Nubian aquifer using GRACE data

Gravity Recovery and Climate Experiment (GRACE) level two (L2) data is used in estimating the groundwater storage changes (GWSC) in the Nubian Sandstone Aquifer System (NSAS). This set of data consists of spherical harmonics coefficients with specific degree and order. The GRACE data is de-correlated using a sixth degree polynomial in order to reduce the effect of the noise error resulting from the correlation between the spherical harmonics coefficients with the same degree parity. The GRACE estimates of GWSC are smoothed using Gaussian filter with half width of 1000 km. This half width is chosen in order to maximize the correlation between the GRACE estimates of GWSC and previous modeling results of the NSAS. The loss in groundwater storage occurring in each of the four countries sharing the NSAS is calculated to assess the sustainability of using the NSAS as a water resource in each country. The overarching finding in this study is that NSAS is losing its groundwater storage at a very high rate. Also, it is found that Egypt is the fastest in losing its groundwater storage from the NSAS. This loss of groundwater storage in Egypt may not necessarily be resulting from in-country extractions because of the trans-boundary nature of this aquifer. The GRACE-based estimates are found to be close to available data and previous modeling results of the NSAS.