Estimation of Spatial Groundwater Recharge Using WetSpass Model for East Wasit Province, Iraq

Groundwater is an important water source, especially in arid and semi-arid areas. Recharge is critical to managing and analyzing groundwater resources despite estimation difficulty due to temporal and spatial change. The study aim is to estimate annual groundwater recharge for the eastern Wasit Province part, Iraq. Where suffers from a surface water shortage due to the region's high elevation above Tigris River water elevation by about 60 m, it is necessary to search for alternative water sources, such as groundwater use. The spatially distributed WetSpass model was used to estimate the annual recharge. The inputs for the model were prepared using the ARC-GIS program, which includes the topography and slope grid, soil texture grid, land use, groundwater level grid, and meteorological data grids for the study area for the period (2014-2019). The result shows that the annual recharge calculated using the WetSpass model (2014-2019) varied of 0 to 65.176 mm/year at an average of 27.117 mm/year, about 10.8%, while the rate of the surface runoff was 5.2% and Evapotranspiration formed 83.33% of the annual rainfall rate of 251.192 mm. The simulation results reveal that the WetSpass model simulates the components of the hydrological water budget correctly. For managing and planning available water resources, a best grasp of the simulation of long-range average geographical distribution around the water balance components is beneficial.

HydroPy (v1.0): a new global hydrology model written in Python

Global hydrological models (GHMs) are a useful tool in the assessment of the land surface water balance. They are used to further the understanding of interactions between water balance components and their past evolution as well as potential future development under various scenarios. While GHMs have been part of the hydrologist's toolbox for several decades, the models are continuously being developed. In our study, we present the HydroPy model, a revised version of an established GHM, the Max Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the new model requires much less effort in maintenance, and due to its flexible infrastructure, new processes can be easily implemented. Besides providing a thorough documentation of the processes currently implemented in HydroPy, we demonstrate the skill of the model in simulating the land surface water balance. We find that evapotranspiration is reproduced realistically for the majority of the land surface but is underestimated in the tropics. The simulated river discharge correlates well with observations. Biases are evident for the annual accumulated discharge; however, they can – at least to some extent – be attributed to discrepancies between the meteorological model forcing data and the observations. Finally, we show that HydroPy performs very similarly to MPI-HM and thus conclude the successful transition from MPI-HM to HydroPy.

Monitoring the water balance of seepage lakes to track regional responses to an evolving climate

Understanding the causes of large fluctuations in lake water levels is important for adaptive resource management. The relatively simple water budgets of small seepage lakes make them potentially useful model systems, provided that key water balance components can be well constrained. Here, spatial variability in measured rates of evaporation (E) and precipitation (P) at the whole lake scale was investigated, and the effect on daily and seasonal water balance estimates was quantified. To estimate spatial variability, triplicate sensor platforms were deployed on and near an 18 ha seepage lake. Lake stage (S) was monitored at a single node in the lake. The water balance was closed by estimating net groundwater seepage (Gnet) analytically as Gnet = ∆S – (P – E). Instrumentation on a second seepage lake was maintained by citizen scientists to assess the potential for more widespread sensor deployments. Data were collected every 30-minutes for six months. The results indicate that low-cost sensor networks with single nodes to measure E, P and ∆S provide well-constrained water budgets at daily and seasonal time scales.

Trends and variability of water balance components over a tropical savanna and Eucalyptus forest in Australia

In this paper, the long-term dynamics of water balance components in two different contrasting ecosystems in Australia were simulated with an ecohydrological model (WAter Vegetation Energy and Solute modelling (WAVES)) over the period 1950–2015. The selected two ecosystems are woodland savanna in Daly River and Eucalyptus forest in Tumbarumba. The WAVES model was first manually calibrated and validated against soil water content measured by cosmic-ray probe and evapotranspiration measured with eddy flux techniques. The calibrated model was then used to simulate long-term water balance components with observed climate data at two sites. Analyzing the trends and variabilities of potential evapotranspiration and precipitation is used to interpret the climate change impacts on ecosystem water balance. The results showed that the WAVES model can accurately simulate soil water content and evapotranspiration at two study sites. Over the period of 1950–2015, annual evapotranspiration at both sites showed decreasing trends (−1.988 mm year−1 in Daly and −0.381 mm year−1 in Tumbarumba), whereas annual runoff in Daly increased significantly (5.870 mm year−1) and decreased in Tumbarumba (–0.886 mm year−1). It can be concluded that the annual runoff trends are consistent with the rainfall trends, whereas trends in annual evapotranspiration are influenced by both rainfall and potential evapotranspiration. The results can provide evidence for controlling the impacting factors for different ecosystems under climate change.

Correction: Gulakhmadov et al. Evaluation of the CRU TS3.1, APHRODITE_V1101, and CFSR Datasets in Assessing Water Balance Components in the Upper Vakhsh River Basin in Central Asia. Atmosphere 2021, 12, 1334

The authors were not aware of errors that were made during the proofreading phase and would hence wish to make the below-mentioned corrections to this paper [...]

Assessment of water resources system in Qena governorate, Upper Egypt under different hydrological and agronomic conditions

This paper assessed the current water resources system and two future scenarios in Qena governorate by developing Water Balance (WB Model) and Water Security Quality-based Index (WSQI). First scenario presented 25% reduction in Nile flow, while second scenario suggested adaptation measures to comply with flow reduction. The measures included leveling 100,000 feddans, serving 70,000 feddans with sprinkler irrigation, and lining 2,977 km of canals. The WB Model estimated water balance components. The WSQI was a new index suitable for Egypt's conditions considering water quality. The water supply from High Aswan Dam (HAD) was predicted by the BlueM model for hydrological simulations of Nasser Lake. The study found that the current water shortage was fulfilled by drainage reuse and shallow groundwater, and the WQSI indicated a low water insecurity. The flow reduction increased water shortage and reuse quantity. As a result, the WSQI indicated high water insecurity. The suggested measures improved agricultural water use efficiency from 51% to 63%, reduced water shortage, and improved water insecurity level from high to medium. This study concluded that adaptation measures can improve the future water system and water security in Qena governorate. The study recommended upscaling WSQI use for the entire country.

Estimation of Spatial and Temporal Groundwater Balance Components in Khadir Canal Sub-Division, Chaj Doab, Pakistan

Evaluation of the spatial and temporal distribution of water balance components is required for efficient and sustainable management of groundwater resources, especially in semi-arid and data-poor areas. The Khadir canal sub-division, Chaj Doab, Pakistan, is a semi-arid area which has shallow aquifers which are being pumped by a plethora of wells with no effective monitoring. This study employed a monthly water balance model (water and energy transfer among soil, plants, and atmosphere)—WetSpass-M—to determine the groundwater balance components on annual, seasonal, and monthly time scales for a period of the last 20 years (2000–2019) in the Khadir canal sub-division. The spatial distribution of water balance components depends on soil texture, land use, groundwater level, slope, and meteorological conditions. Inputs for the model included data on topography, slope, soil, groundwater depth, slope, land use, and meteorological data (e.g., precipitation, air temperature, potential evapotranspiration, and wind speed) which were prepared using ArcGIS. The long-term average annual rainfall (455.7 mm) is distributed as 231 mm (51%) evapotranspiration, 109.1 mm (24%) surface runoff, and 115.6 mm (25%) groundwater recharge. About 51% of groundwater recharge occurs in summer, 18% in autumn, 14% in winter, and 17% in spring. Results showed that the WetSpass-M model properly simulated the water balance components of the Khadir canal sub-division. The WetSpass-M model’s findings can be used to develop a regional groundwater model for simulation of different aquifer management scenarios in the Khadir area, Pakistan.

Assessment of the ParFlow–CLM CONUS 1.0 integrated hydrologic model: evaluation of hyper-resolution water balance components across the contiguous United States

Recent advancements in computational efficiency and Earth system modeling have awarded hydrologists with increasingly high-resolution models of terrestrial hydrology, which are paramount to understanding and predicting complex fluxes of moisture and energy. Continental-scale hydrologic simulations are, in particular, of interest to the hydrologic community for numerous societal, scientific, and operational benefits. The coupled hydrology–land surface model ParFlow–CLM configured over the continental United States (PFCONUS) has been employed in previous literature to study scale-dependent connections between water table depth, topography, recharge, and evapotranspiration, as well as to explore impacts of anthropogenic aquifer depletion to the water and energy balance. These studies have allowed for an unprecedented process-based understanding of the continental water cycle at high resolution. Here, we provide the most comprehensive evaluation of PFCONUS version 1.0 (PFCONUSv1) performance to date by comparing numerous modeled water balance components with thousands of in situ observations and several remote sensing products and using a range of statistical performance metrics for evaluation. PFCONUSv1 comparisons with these datasets are a promising indicator of model fidelity and ability to reproduce the continental-scale water balance at high resolution. Areas for improvement are identified, such as a positive streamflow bias at gauges in the eastern Great Plains, a shallow water table bias over many areas of the model domain, and low bias in seasonal total water storage amplitude, especially for the Ohio, Missouri, and Arkansas River basins. We discuss several potential sources for model bias and suggest that minimizing error in topographic processing and meteorological forcing would considerably improve model performance. Results here provide a benchmark and guidance for further PFCONUS model development, and they highlight the importance of concurrently evaluating all hydrologic components and fluxes to provide a multivariate, holistic validation of the complete modeled water balance.

Changing Causes of Drought in the Urmia Lake Basin—Increasing Influence of Evaporation and Disappearing Snow Cover

The water level of the Urmia Lake Basin (ULB), located in the northwest of Iran, started to decline dramatically about two decades ago. As a result, the area has become the focus of increasing scientific research. In order to improve understanding of the connections between declining lake level and changing local drought conditions, three common drought indices are employed to analyze the period 1981–2018: The Standard Precipitation Index (SPI), the Standard Precipitation-Evaporation Index (SPEI), and the Standardized Snow Melt and Rain Index (SMRI). Although rainfall is a significant indicator of water availability, temperature is also a key factor since it determines rates of evapotranspiration and snowmelt. These different processes are captured by the three drought indices mentioned above to describe drought in the catchment. Therefore, the main objective of this paper is to provide a comparative analysis of drought over the ULB by incorporating different drought indices. Since there is not enough long-term observational data of sufficiently high density for the ULB region, ECMWF Reanalysis data version 5(ERA5) has been used to estimate SPI, SPEI, and SMRI drought indicators. These are shown to work well, with AUC-ROC > 0.9, in capturing different classes of basin drought characteristics. The results show a downward trend for SPEI and SMRI (but not for SPI), suggesting that both evaporation and lack of snowmelt exacerbate droughts. Owing to the increasing temperatures in the basin and the decrease in snowfall, drought events have become particularly pronounced in the SPEI and SMRI time series since 2010. No significant SMRI drought was detected prior to 1995, thus indicating that sufficient snowfall was available at the beginning of the study period. The study results also reveal that the decrease in lake water level from 2010 to 2018 was not only caused by changes in the water balance components, but also by unsustainable water management.

On the selection of precipitation products for the regionalisation of hydrological model parameters

Over the past decades, novel parameter regionalisation techniques have been developed to predict streamflow in data-scarce regions. In this paper, we examined how the choice of gridded daily precipitation (P) products affects the relative performance of three well-known parameter regionalisation techniques (spatial proximity, feature similarity, and parameter regression) over 100 near-natural catchments with diverse hydrological regimes across Chile. We set up and calibrated a conceptual semi-distributed HBV-like hydrological model (TUWmodel) for each catchment, using four P products (CR2MET, RF-MEP, ERA5, and MSWEPv2.8). We assessed the ability of these regionalisation techniques to transfer the parameters of a rainfall-runoff model, implementing a leave-one-out cross-validation procedure for each P product. Despite differences in the spatio-temporal distribution of P, all products provided good performance during calibration (median Kling–Gupta efficiencies (KGE′s) > 0.77), two independent verification periods (median KGE′s >0.70 and 0.61, for near-normal and dry conditions, respectively), and regionalisation (median KGE′s for the best method ranging from 0.56 to 0.63). We show how model calibration is able to compensate, to some extent, differences between P forcings by adjusting model parameters and thus the water balance components. Overall, feature similarity provided the best results, followed by spatial proximity, while parameter regression resulted in the worst performance, reinforcing the importance of transferring complete model parameter sets to ungauged catchments. Our results suggest that (i) merging P products and ground-based measurements does not necessarily translate into an improved hydrologic model performance; (ii) the spatial resolution of P products does not substantially affect the regionalisation performance; (iii) a P product that provides the best individual model performance during calibration and verification does not necessarily yield the best performance in terms of parameter regionalisation; and (iv) the model parameters and the performance of regionalisation methods are affected by the hydrological regime, with the best results for spatial proximity and feature similarity obtained for rain-dominated catchments with a minor snowmelt component.