Hydrological modeling for water management in large watersheds requires accurate spatially-distributed rainfall time series. In case of low coverage density of ground-based measurements, gridded ...precipitation products (GPPs) from merged satellite-/gauge-/model-based rainfall products constitute an attractive alternative. The quality of which must, nevertheless, be verified. The objective of this study was to evaluate, at different time scales, the reliability of 6 GPPs against a 2-year record from a network of 14 rainfall gauges located in the Ankavia catchment (Madagascar). The GPPs considered in this study are the African Rainfall Estimate Climatology (ARC2), the Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), the European Centre Medium-Range Weather Forecasts ECMWF Reanalysis on global land surface (ERA5-Land), the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement V06 Final (IMERG), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS), and the African Rainfall Estimation (RFEv2) products. The results suggest that IMERG (R2 = 0.63, slope of linear regression a = 0.96, root mean square error RMSE = 12 mm/day, mean absolute error MAE = 5.5 mm/day) outperforms other GPPs at the daily scale, followed by RFEv2 (R2 = 0.41, a = 0.94, RMSE = 15 mm/day, MAE = 6 mm/day) and ARC2 (R2 = 0.30, a = 0.88, RMSE = 16 mm/day, MAE = 6.7 mm/day). All GPPs, with the exception of the ERA5, overestimate the ‘no rain’ class (0–0.2 mm/day). ARC2, IMERG, PERSIANN, and RFEv2 all underestimate rainfall occurrence in the 0.2–150 mm/day rainfall range, whilst CHIRPS and ERA5 overestimate it. Only CHIRPS and PERSIANN could estimate extreme rainfall (>150 mm/day) satisfactorily. According to the Critical Success Index (CSI) categorical statistical measure, IMERG performs quite well in detecting rain events in the range of 2–100 mm/day, whereas PERSIANN outperforms IMERG for rain events larger than 150 mm/day. Because it performs best at daily scale, only IMERG was evaluated for time scales other than daily. At the yearly and monthly time scales, the performance is good with R2 = 0.97 and 0.87, respectively. At the event time scale, the probability distribution function PDF of rain gauge values and IMERG data show good agreement. However, at an hourly time scale, the correlation between ground-based measurements and IMERG data becomes poor (R2 = 0.20). Overall, the IMERG product can be regarded as the most reliable gridded precipitation source at monthly, daily, and event time scales for hydrological applications in the study area, but the poor agreement at hourly time scale and the inability to detect extreme rainfall >100 mm/day may, nevertheless, restrict its use.
•We explored the hydrological alterations and assessed possible explaining factors.•Trend and CCM analysis were used to understand the hydrological response.•The Medjerda is highly influenced by ...agricultural activities and climate factors.
The Medjerda is a transboundary catchment located in North-Eastern Algeria and shared with Tunisia.
In this study, we explore the causes of hydrological alteration of streamflow in a sub-catchment of the Medjerda in Algeria. The hydrological alteration was explored through the application of Mann-Kendall test based on possible explanatory factors, namely, precipitation, evapotranspiration, temperature, irrigation, and Normalized Difference of Vegetation Index (NDVI). Furthermore, the causal factors of streamflow variation were addressed using Convergent Cross Mapping (CCM) method.
Results of the trend analysis yield that the streamflow is altered during the period 1981−2012. This is consistent with the trends of the possible explanatory factors of this alteration. The Convergent Cross Mapping (CCM) method showed that streamflow alteration is unidirectionally caused by changes in patterns of precipitation, temperature, evapotranspiration, irrigation, and NDVI, and that there is little feedback from streamflow alteration to these causing factors. Overall, our assessment showed that the method used to identify the causal relationships in dynamical systems based on the CCM algorithm is suitable for exploring the drivers of the hydrologic alteration in multivariate time series, in particular when nonlinear dynamics determine the system.
Recent technological progress in water management of hydrosystems has been made to deploy efficient and effective water quality monitoring systems (WQMS). Among these, a citizen science (CS)-based ...water quality monitoring (WQM) program using test strips is considered as a smart tool that may aid in the production of reliable, continuous, and comprehensive data on the water quality resources of hydrosystems over a broad range of spatial and temporal scales. In this case study, the objective is to evaluate the performance of a CS-based WQM for nitrates assessment using test water quality strips for the Medjerda watershed in Northern Tunisia. Overall, 137 samples were collected from 24 sampling sites and were analyzed by 33 participants. Citizens involved in the program were regrouped in five citizen types according to their socio-economic characteristics. Statistical tests, analysis of variance (ANOVA) and multiple correspondence analyses (MCA) were achieved to survey the goodness of fit of CS as a contribution to data collection in terms of the socio-economic profile of the participant. The results show that this tool could be reliable for obtaining the levels of nitrate in water samples. Water quality test trips can conveniently be used by citizens for WQM of nitrates when they are rigorously following the manufacturer’s instructions. Additional efforts in communication and training could help to improve the performance of this CS-WQM program for nitrate in the Medjerda watershed.
As recently created, the landfill site of Oujda, Morocco receives an annual flow of municipal solid wastes of 140000 tons. It became clear that the leachate storage ponds were undersized compared to ...the actually emanating flows. With no adequate treatment, the storage time of leachates in deep and anaerobic ponds increase and produce olfactory nuisances directly affecting the air quality of the nearest agglomerations. The monitoring of leachate flows during a year, showed the daily average production of 126 m3 (annual cumulative leachate is 46800 m3). Thus, highest volumes were recorded during the summer season (4716 m3 in July 4945 m3 in August, and 4927 m3 in September) with a monthly average rate of 3700 m3. In addition, the monitoring of leachate flows exhibits annual variations. Simultaneously, the MSW's typology and moisture content study showed the dominance of organic matter (73%) and high moisture content (63.5%). The results obtained are an essential asset for any decision in order to achieve appropriate leachates treatment with a possibility of recirculation into the landfill cells to enhance removal of their toxic contents.
Understanding the hydrological behavior of watersheds (WS) and their driving factors is crucial for sustainable water resources management. However, at large scales, this task remains challenging due ...to the spatial heterogeneity in landscapes, topography and morphology (T), land cover (LC), geology (G), and soil properties (S). In this context, the aim of this study was to identify the key factors that influence the hydrological signatures of four watersheds: Ankavia (WS1: 55% forest cover), Ankaviabe (WS2: 77% forest cover), Sahafihitry (WS3: 41% forest cover), and Antsahovy (WS4: 48% forest cover), over a 10-month study period. These catchments are located within the SAVA region of northeastern Madagascar and have a humid tropical climate. We investigated the relationship between selected catchment descriptors and hydrological signatures by using a Pearson coefficient-based correlation matrix. More specifically, catchment descriptors (extracted from T, LC, G, and S) were correlated with the following hydrological signatures: base flow index (BFI), mean runoff coefficient (rc), mean peak flow (Qp), mean runoff event time scales (ts), high flows (Q5), low flows (Q95), and mean discharge (q_mean). The analysis revealed that land cover, soil properties, and geology seem to be the best predictors for BFI and Q95, while soil properties mainly govern rc, Qp, Q5, ts, and q_mean. These findings provide valuable insights into the key drivers of hydrological behavior that can inform water resource management strategies. In particular, WS2 exhibits better flood buffering capacity but also experiences lower base flows in the dry season, potentially due to higher evapotranspiration. Conversely, WS3 and WS4 (and to a lesser extent WS1) have lower flood buffering capacity, but these watersheds encounter less pronounced low flows in the dry season due to higher BFIs, possibly attributable to lower evapotranspiration rates. The results underscore the importance of responsible land use practices and conservation efforts, which are essential for the sustainable development of the region. By incorporating these practices into water management strategies, we can help ensure a more stable and reliable water supply for communities and ecosystems within the region.
In this study, groundwater potential was mapped for a Mediterranean catchment using remote sensing techniques, geographical information systems (GIS), and the fuzzy analytical hierarchy (FAHP) ...process. Seven environmental factors were considered to influence groundwater potential, including soil type, lithology, precipitation, land use/cover, slope, lineament density, and drainage density. A FAHP method was implemented to calculate the weight of each factor and each class in the groundwater potential. The FAHP confusion matrix was established by eliciting opinions of local experts on factors that drive groundwater potential in this area. A weighted overlay was made in Arc-GIS™ for producing the final groundwater potential map. Three groundwater potential classes were considered (low, moderate, strong). Areas of very high potential represent 107.09 km
2
(8%) of the total surface of the basin and are located in alluvial and calcareous formations of a high density of lineament and in areas with a low slope which promotes rapid infiltration. About 1022.124 km
2
(71%) of the surface of the sub-catchment is characterized by a moderate to strong potential, while the remainder 305.945 km
2
(21%) is characterized by a low potential. The results of the classification are validated by establishing the receiver operating characteristic (ROC) curve using 61 data from the wells located in the study area. The area under curve (AUC) yields 75.5% demonstrating the effectiveness of the method in identifying groundwater potential areas.
Groundwater pollution risk modelling is an important asset to improve groundwater management and protection. In this study, we assess the temporal dynamics of groundwater pollution risk at the ...continental scale, using the DRASTIC model. The approach was developed using continental-scale data on soil properties, topography, land use, geology, hydrogeology, and climate with a resolution of 15 × 15 km2. We compared continental-scale groundwater pollution risk for the years 1990, 2000, and 2010. The results showed significant inter-annual variations of the spatial distribution of pollution risk. Changes were mainly concentrated in the area of the Nile Delta, around the Lake Victoria, in North Africa, and in coastal West Africa (predominately in Nigeria). We found that the increase in pollution risk was mainly related to the increase in the population density in these regions. The proposed methodology for modelling the temporal dynamics of groundwater pollution risk could support the monitoring of the Sustainable Development Goal 6, which focus in particular on the preservation of the freshwater resources against future threats.
Evapotranspiration (ET) controls the flux between the land surface and the atmosphere. Assessing the ET ecosystems remains a key challenge in hydrology. We have found that the ET water mass loss can ...be directly inferred from continuous gravity measurements: as water evaporates and transpires from terrestrial ecosystems, the mass distribution of water decreases, changing the gravity field. Using continuous superconducting gravity measurements, we were able to identify daily gravity changes at the level of, or smaller than, 10−9 nm s−2 (or 10−10 g) per day. This corresponds to 1.7 mm of water over an area of 50 ha. The strength of this method is its ability to enable a direct, traceable and continuous monitoring of actual ET for years at the mesoscale with a high accuracy.
Key Points
Continuous gravity measurements reveal the evapotranspiration of a forested ecosystem at the mesoscale (~50 ha)
An oak‐beech forest evaporates 1.7 mm of water during sunny summer days
Ground gravity is now able to isolate regular signals at the level of a few tenths of millimeters of water
This data article provides high spatial resolution (1 cm) datasets and related figures of the penetrometer resistance (PR) and soil bulk density (BD) data of nine agricultural 50 × 160 cm soil ...profiles exposed to three tillage treatments and including a wheel track. Soil treatments are moldboard plowing (MP), deep loosening (DL), and minimum tillage (MT). It also provides bulk density data, soil moisture content at various suctions and the parameters of van Genuchten's model for 27 soil cores, and saturated hydraulic conductivity (Ks) of 49 soil cores. Both sample sets were sampled to cover the profile heterogeneity in two agricultural plots subjected to moldboard plowing and minimum tillage. Examples of reuse potential include (i) the use of these spatially explicit data in studies seeking to understand better and integrate the effect of treatment and machine traffic-induced soil structure in soil hydraulic and soil physical quality, and (ii) the development of pedotransfer functions with data incorporating the soil structural heterogeneity. This Data in Brief article complements the companion paper by Alonso et al. (2021) “A hybrid method for characterizing tillage-induced soil physical quality at the profile scale with fine spatial detail” in Soil and Tillage Research1.
We analyze the common surface reflection and full‐wave inversion methods to retrieve the soil surface dielectric permittivity and correlated water content from air‐launched ground‐penetrating radar ...(GPR) measurements. In the full‐wave approach, antenna effects are filtered out from the raw radar data in the frequency domain, and full‐wave inversion is performed in the time domain, on a time window focused on the surface reflection. Synthetic experiments are performed to investigate the most critical hypotheses on which both techniques rely, namely, the negligible effects of the soil electric conductivity (σ) and layering. In the frequency range 1–2 GHz we show that for σ > 0.1 Sm−1, significant errors are made on the estimated parameters, e.g., an absolute error of 0.10 in water content may be observed for σ = 1 Sm−1. This threshold is more stringent with decreasing frequency. Contrasting surface layering may proportionally lead to significant errors when the thickness of the surface layer is close to one fourth the wavelength in the medium, which corresponds to the depth resolution. Absolute errors may be >0.10 in water content for large contrasts. Yet we show that full‐wave inversion presents valuable advantages compared to the common surface reflection method. First, filtering antenna effects may prevent absolute errors >0.04 in water content, depending of the antenna height. Second, the critical reference measurements above a perfect electric conductor (PEC) are not required, and the height of the antenna does not need to be known a priori. This averts absolute errors of 0.02–0.09 in water content when antenna height differences of 1–5 cm occur between the soil and the PEC. A laboratory experiment is finally presented to analyze the stability of the estimates with respect to actual measurement and modeling errors. While the conditions were particularly well suited for applying the common reflection method, better results were obtained using full‐wave inversion.
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