Water Balance Model Research Articles

Evapotranspiration and crop coefficients of sprinkler-irrigated aerobic rice in southern Brazil using the SIMDualKc water balance model

Evapotranspiration and crop coefficients of sprinkler-irrigated aerobic rice in southern Brazil using the SIMDualKc water balance model

Determination of the minimum soil infiltration rate of sunken green space considering the annual runoff collection ratio, sunken depth and sunken green space area of Hefei city, China.

Sunken green space is one of the urban rainwater collection facilities, which belongs to Low Impact Development (LID) techniques. It plays a key role in the construction of sponge city, and the amount of runoff collection is usually affected by the area of the sunken green space, the infiltration rate of the soil, and the annual runoff collection rate. To determine the minimum soil infiltration rate of sunken green space considering the annual runoff collection ratio of sponge cities, this paper selects a residential district in Hefei city, China, as the case study. Based on 45 years of precipitation data, the designed rainfall corresponding to annual runoff collection ratios of 75%, 80% and 85% is 21.3 mm, 23.4 mm and 27.5 mm, respectively. The characteristics of rainfall infiltration in sunken green space are analyzed by using the water balance model and runoff yield and conflux model. The results reveal that the soil infiltration rate is 1.16×10-4 cm/s~3.88×10-3 cm/s when the sunken depth is 0.1 m~0.3 m and that the ratio of green space area is 5%~25%. The runoff collection of the reconstructed sunken green space is 2.87 times and 1.98 times that of the nonsunken green space and the nonreconstructed sunken green space, respectively. That is to say, under the comprehensive performance of the sunken depth, sunken green space area, the steady soil infiltration rater of the reconstructed sunken green space cannot be less than the value obtained in this paper. Otherwise, the requirements of annual total runoff reduction ratio of the sponge city cannot be met. Therefore, this study provides references for realizing the ratio of annual runoff collection and sponge city construction in similar urban areas. It can also be applied to optimal selection of sunken green space in some sponge city projects.

Estimating Climate Change’s Impacts on the Recharge of an Ungauged Tropical Aquifer (Togolese Coastal Sedimentary Basin)

The aquifers of the Togolese coastal sedimentary basin are the principal sources of water for almost half of the country’s population. These aquifers’ features have not been adequately monitored and studied. The resource is threatened by human activities, notably agriculture, industry, and withdrawals for drinking water supplies. This situation is exacerbated by the potential effects of climate change. For this research, a basin-scale study was conducted to estimate current groundwater recharge and its future evolution in response to climate change. A recharge model based on Thornthwaite–Mather balance equations using runoff coefficients characterizing land use was fed with current and future climate data from an optimistic scenario (RCP 4.5) and a pessimistic scenario (RCP 8.4). Despite the associated uncertainties, the soil–water balance model at monthly time steps predicts a recharge of 3 to 455 mm per year from 2020 to 2039, and 40 to 420 mm per year from 2040 to 2059 under the optimistic RCP 4.5 scenario. According to the pessimistic RCP 8.5 scenario, the recharge will range between 16 and 515 mm per year from 2020 to 2049 and from 1 to 467 mm per year between 2040 and 2059. As a result, the basin’s groundwater recharge range, which is currently 47 to 225 mm, will significantly increase. This study provides a scientific basis for the sustainable management of groundwater in the Togolese coastal sedimentary basin. The recharge of the groundwater in the basin will increase regardless of the climate scenario and will support future development in the Togolese coastal sedimentary basin.

Scaling from global to regional river flow with global hydrological models: Choice matters

High-resolution global flow discharge datasets are critical to understand the terrestrial water cycle and river ecosystem services. Recently, a number of global hydrological models have been developed to capture global river flow dynamics at locally relevant scales. However, the relative accuracy of these simulated flow discharges is largely unknown. In this paper, using the largest observed streamflow datasets from > 26,000 gauging stations, we evaluated the performance of monthly and sub-monthly flow variation (1980–2014) generated from five major global hydrological models, Catchment-based Macro-scale Floodplain model (CaMa-Flood), Global Flood Awareness System (GloFAS-reanalysis), Global Reach-level Flood Reanalysis (GRFR), PCRaster GLOBal Water Balance model (PCR-GLOBWB), and Water Global Assessment and Prognosis (WaterGAP). Significant spatial heterogeneity in model performance was identified. We found that estimates by all five discharge datasets have a relatively high correlation with the observations (medians > 0.6). But none of them showed adequate correlations between simulated and observed flows for systems in Southwest or Central U.S.A., South Africa, or South Australia. Across all models, overestimation of monthly mean flow was more common than underestimation and high flows at a sub-monthly scale were more accurately characterized than low flows. Performance of all models was poor in Africa and Oceania. No single model performed universally best at all gauging stations, but GRFR showed the best estimate at around 40 % of the locations. None of the models provided satisfying estimates for rivers and streams in arid regions. We also found a significant negative effect of flow regulation on the predictive accuracy of all models. Our study highlights the importance of thorough evaluation of global discharge datasets before their local and regional application and provides guidance for future enhancement of global hydrological models.

A new algorithm for the energy–water balance model to quantitatively reconstruct Holocene precipitation and vegetation: a case study from Dali Lake, North China

Quantitatively reconstructing precipitation is an important component of paleoclimate research. The mean annual precipitation (MAP) of a closed-basin lake can be estimated by the energy–water balance model (EWBM). The EWBM can be divided into linear and nonlinear models, with determination of evaporation over water and land surface being the main components. However, the influence of vegetation changes on different models and the potential of the models to reconstruct vegetation remain unclear. Dali Lake, a closed-basin lake in the marginal region of the East Asian summer monsoon (EASM), is selected as the study region to test the feasibility of a new algorithm, i.e., the comparative method. This method is performed by comparing the reconstructed MAPs given by linear and nonlinear models for each stepwise reduced or increased forest fraction until both MAPs are approximately equal within the error range. The results indicate that the linear model is more sensitive to vegetation changes than the nonlinear model; however, both linear and nonlinear models can obtain the modern MAP correctly. Additionally, the comparative method can successfully determine the vegetation cover. Using the reported paleolake levels of Dali Lake, we calculate the Holocene MAP and vegetation of the Dali Lake basin. The results show that the early and middle Holocene MAP obtained by the comparative method is ∼10 mm higher than that obtained by the nonlinear model, while the difference in the late Holocene is not insignificant. The reconstructed vegetation is generally consistent with the pollen-indicated vegetation changes in the Dali Lake region and the monsoon marginal zone in North China. Our study suggests that both linear and nonlinear models can provide reliable MAP values for basins with known vegetation. For basins with unknown vegetation, the nonlinear model with variable parameters or the more advantageous comparative method is preferred. In cases where the basin mainly consists of two vegetation types, the comparative method enables to reconstruct the fraction of two vegetation types.

Agricultural drought assessment in dry zones of Tolima, Colombia, using an approach based on water balance and vegetation water stress

Soil water balance is an essential element to consider for the management of droughts and agricultural land use. It is important to evaluate the water consumption of a crop in each of its phenological phases and the status of water reserves during critical hydrologic periods. This study developed an agricultural drought index (Standardized Soil Moisture Deficit Index - SMODI) conceptualized with a water balance model considering the vegetation stress caused by soil moisture deficit. This contribution was based on meteorological information, soil moisture from satellite images, hydrophysical properties of the soil and crop evapotranspiration. Information from 61 weather stations located in the dry zone of Tolima was used for estimating the water balance. SMODI was compared with the most common drought indexes: Standardized Precipitation - Evapotranspiration Index (SPEI), the Palmer Self-Calibrated Drought Index (scPDSI), and other eleven macroclimatic indexes. Pearson's correlation coefficients (r), Tukey's test, and analysis of variance were applied to analyze the degree of association between SMODI and the contrasting indexes on a quarterly basis. SMODI considers factors influencing soil moisture distribution and retention and the water stress thresholds that plants have evolved to withstand during drought periods. Consequently, this integrated approach enhances the assessment of agricultural drought by relying on pertinent physical processes. SMODI identified extremely dry, severe, moderate and normal drought 5 %, 3 %, 20 % and 72 % respectively conditions in areas characterized by Entisols, Inceptisols, and Andisols, where rice and fruit crops and pasturelands are cultivated. The SMODI has a good correlation with macroclimatic indexes (0.70 < r < 0.74).

A review of existing methods for predicting leachate production from municipal solid waste landfills.

Landfilling is one of the predominant methods of municipal solid waste (MSW) disposal worldwide, while the generation of leachate, a kind of toxic wastewater, is among the primary factors behind landfill instability and environmental contamination problems. Precise prediction of leachate production is crucial to landfill safety evaluation and design. This paper presents a comprehensive review of methods for predicting leachate production from MSW landfills. Firstly, compositional characteristics of MSW and leachate generation mechanism are analysed. Factors influencing leachate production are summarised based on the generation mechanism, including the components of MSW, climatic conditions, landfill structure, and environmental factors. Then, we classified the existing methods for predicting leachate production into four categories: water balance formula, water balance model, empirical formula, and artificial intelligence model methods. Advantages, disadvantages, and applicability of different leachate production prediction methods are compared and analysed. Furthermore, limitations in the existing leachate production prediction methods for MSW landfills and scope for future research are discussed.

Quantifying water loss in leaky micro-dam reservoir through water balance analysis and high-resolution water level data modeling

Abstract This study aimed to assess the runoff, recharge, and response of a shallow aquifer to leakage from the Arato micro-dam reservoir (MDR). The assessment was conducted using the Soil Conservation Service Curve Number (SCS-CN), soil moisture balance (SMB), and diver (automatic data logger) measurements in both the MDR and a shallow hand-dug well. Recharge was estimated using the chloride mass balance (CMB) and water table fluctuation (WTF) methods. The results revealed that the annual runoff from the catchment was 48.8 mm, which accounted for approximately 0.71 million m3. The yearly groundwater recharge was estimated to be 104, 92.8, and 100 mm using the SMB, CMB, and WTF methods, respectively. Furthermore, the water balance model of the Arato MDR indicated a leakage rate of 13.2 mm/day. It is noteworthy that the estimated leakage exceeded the seepage initially anticipated during the project's design phase (9,965 m3/year). This research project highlights the significance of utilizing local climatic and physical data from the specific watershed under investigation when planning reservoirs and other water resources. It also underscores the importance of conducting thorough site investigations to accurately quantify hydraulic conductivity for leakage estimation purposes.

An inter-comparison of approaches and frameworks to quantify irrigation from satellite data

Abstract. This study provides the first inter-comparison of different state-of-the-art approaches and frameworks that share a commonality in their utilization of satellite remote-sensing data to quantify irrigation at a regional scale. The compared approaches vary in their reliance on either soil moisture or evapotranspiration data or their joint utilization of both. The two compared frameworks either extract irrigation information from residuals between satellite observations and rainfed hydrological models in a baseline framework or use soil water balance modeling in a soil-moisture-based inversion framework. The inter-comparison is conducted over the lower Ebro catchment in Spain where observed irrigation amounts are available for benchmarking. Our results showed that within the baseline framework, the joint approach using both soil moisture and evapotranspiration (ET) remote-sensing data only differed by +37 mm from the irrigation benchmark (922 mm) during the main irrigation season over 2 years and by +47 and −208 mm for approaches relying solely on soil moisture and ET, respectively. A comparison of the different frameworks showed that the main advantage of the more complex baseline framework was the consistency between soil moisture and ET components within the hydrological model, which made it unlikely that either one ended up representing all irrigation water use. However, the simplicity of the soil-moisture-based inversion framework, coupled with its direct conversion of soil moisture changes into actual water volumes, effectively addresses the key challenges inherent in the baseline framework, which are associated with uncertainties related to an unknown remote-sensing observation depth and the static depth of the soil layers in a conceptual model. The performance of the baseline framework came closest to the irrigation benchmark and was able to account for the precipitation input, which resulted in more plausible temporal distributions of irrigation than what was expected from the benchmark observations.

Advancing isotope‐enabled hydrological modelling for ungauged calibration of data‐scarce humid tropical catchments

AbstractRealistic projections of the future climate and how this translates to water availability is crucial for sustainable water resource management. However, data availability constrains the capacity to simulate streamflow and corresponding hydrological processes. Developing more robust hydrological models and methods that can circumvent the need for large amounts of hydro‐climatic data is crucial to support water‐related decisions, particularly in developing countries. In this study, we use natural isotope tracers in addition to hydro‐climate data within a newly developed version of the spatially‐distributed J2000iso as an isotope‐enabled rainfall‐runoff model simulating both water and stable isotope (δ2H) fluxes. We pilot the model for the humid tropical San Carlos catchment (2500 km2) in northeastern Costa Rica, which has limited time series, but spatially distributed data. The added benefit of simulating stable isotopes was assessed by comparing different amounts of observation data using three model calibration strategies (i) three streamflow gauges, (ii) three gauges with stream isotopes and (iii) isotopes only. The J2000iso achieved a streamflow Kling–Gupta efficiency (KGE) of 0.55–0.70 across all the models and gauges, but differences in hydrological process simulations emerged when including stable water isotopes in the rainfall‐runoff calibration. Hydrological process simulation varied between the standard J2000 rainfall‐runoff model with a high simulated surface runoff proportion of 37% as opposed to the isotope version with 84%–89% simulated baseflow or interflow. The model solutions that used only isotope data for calibration exhibited differences in simulated interflow, baseflow and model performance but captured bulk water balances with a reasonable match between the simulated and observed hydrographs. We conclude that J2000iso has shown the potential to support water balance modelling for ungauged catchments using stable isotope, satellite and global reanalysis data sets.

Improving the Applicability of Lumped Hydrological Models by Integrating the Generalized Complementary Relationship

AbstractLumped hydrological models (LHMs) are indispensable for water resource planning and environmental studies due to simple structures and robust performances. LHMs commonly focus on runoff processes with crude representations for other hydrological processes, such as evapotranspiration (E). Therefore, these models may yield unrealistic water balance partitioning. The challenge is to enhance the LHMs performance while retaining simplicity. The generalized complementary relationship (GCR) is a simple and robust method for estimating E. This study attempted to incorporate GCR into four widely used LHMs (Australian water balance model, GR2M, SIMHYD, and TANK) to test whether the integrated models (GCR‐LHMs) can improve runoff simulation at little cost to the model structure and data requirement. Original LHMs and integrated GCR‐LHMs were tested in 2112 catchments over various climatic conditions. Results show that the GCR‐LHMs outperform original LHMs in most catchments (77.7 ± 5.0%). In addition, the number of catchments that GCR‐LHMs have qualified performance (i.e., Kling‐Gupta coefficient [KGE] more than 0.5) increased by 10.7 ± 3.6% compared with LHMs. The performance of original and integrated models is dependent on the aridity index and normalized vegetation index. However, the improvement in model performance is less catchment characteristics dependent. These results indicate that incorporating GCR into the LHMs improves the model performance under different climatic and vegetation conditions and justifies the integration. GCR integration with LHMs can improve runoff estimation ability (with higher KGE and R‐Square) while retaining model simplicity and readily available input. These findings are valuable for improving the applicability and accuracy of LHMs.

ASSESSING THE SPATIAL DISTRIBUTION OF WATER BALANCE IN KADUNA STATE, NIGERIA

The purpose of this paper is to examine the spatial distribution of water balance components for Kaduna State. One of the most important outcomes in the water balance equation for any natural area or water body is Evapotranspiration and it is also a crucial component of the hydrologic cycle. In attaining this, monthly data on temperature (T) and rainfall (P) were obtained from NASA (National Aeronautics and Space Administration) twelve remotely sensed stations around Kaduna State for thirty-seven years from 1984 to 2021. Thornthwaite and Mather Water Balance (WB) model was used to estimate WB components i.e., soil moisture (SM), actual evapotranspiration (AET), Water surplus (S) and Runoff (R). Kaduna State was divided into three sub-basins and the result shown peak of R generally occurs during the wet season (i.e., June through November across the three catchment areas) most especially at Kaduna central catchment area in the month of July (1003.85mm). The study further reveals that the bulk of the rains still occur between these months with the peak being reached in July having the peak of rainy season for the three catchment areas with Galma-1378.21mm, Kaduna Central-1443.82mm and Mada- 814.05mm respectively. The area is relatively dry in the months of November–April and has water deficit while Soil moisture recharge takes place from early May to August and mid-May to December is the period of water surplus across the catchment areas. The result of this study provides a reference information on water balance distribution in Kaduna State and utilization for...

Evaluation of Hydrometeorological Characteristics in the Northern Ethiopia, Gerado Catchment

In Northern Ethiopia, land degradation, together with population pressure foster soil erosion. Soil erosion in turn escalates surface runoff which is a serious challenge to agricultural production and economic growth in the region. Understanding the characteristics and dynamics of hydrometeorological variables are important elements in water resources development projects. Present study was carried out to evaluate hydrometeorological characteristics in the Northern Ethiopia, Gerado Catchment. Long term meteorological data such as precipitation, temperature and other climatic factors were collected from existing meteorological stations. Thornthwaite empirical equation and thornthwaite soil water balance models were employed in estimating potential and actual evapotranspiration. The first approach used air temperature as an index of energy available for evapotranspiration. Similarly, groundwater recharge of the catchment was computed as a difference of between outflow and change in a water storage. The runoff of the area was calculated based on the rainfall coefficient, annual precipitation and aerial coverage. On the other hand, groundwater potential (GWP) of the area was mapped based on important selected controlling factors. The result indicated that the annual potential and actual evapotranspiration of the catchment was found to be 755 mm/year and 723 mm/year respectively. The actual evapotranspiration was evaluated and weighted based on the dominant soil textures, depth root soil, and the respective land uses. As result, high evapotranspiration was observed in moderate deep rooted cereal crops and sandy loam soil texture which accounted 48.5% influence. But, cereal crops with moderate deep rooted and clay loam type have low AET (42.2%). Because of absence of gauging stations in the catchment, the volume runoff was computed using the runoff coefficient method. Accordingly, surface runoff from the catchment was calculated to be 120,581,841 cubic meter (m3) or 326 mm. Whereas, the groundwater recharge of the area was also found to be 52,208,159.5 cubic meter (141.5mm). Thus, out of the given mean annual precipitation, 27.6% and 12% of the mean annual rainfall lost because of runoff and recharge and the rest (60.4%) due to evapotranspiration. Regarding GWP suitability mapping, lithology, liniment density and geomorphology were found the most essential factors affecting groundwater mapping. The suitable GWP areas were lied within lithology and geomorphology class. Moreover, areas with flat slope and low lineament density are also located in most rich groundwater areas. Furthermore, installation of rain gauges at appropriate areas are essential for all inclusive and consistent data availability. &#x0D; Keywords: Hydro-meteorological, Gerdo Catchment, groundwater recharge, runoff, evapotranspiration, GWP

Simulation of groundwater-flow dynamics in the U.S. Northern High Plains driven by multi-model estimates of surficial aquifer recharge

There is growing interest in incorporating higher-resolution groundwater modeling within the framework of large-scale land surface models (LSMs), including processes such as three-dimensional flow, variable soil saturation, and surface water/groundwater interactions. Conversely, complex groundwater models (e.g., the U.S. Geological Survey Groundwater-Flow Model, MODFLOW) often use simpler representations of land surface dynamics (e.g., surface vegetation, evapotranspiration, recharge) and may benefit from higher process fidelity and temporal resolutions in these inputs. This study investigates the potential of improving groundwater representation in LSMs and land surface dynamics in MODFLOW through forcing MODFLOW with recharge from LSMs. Groundwater simulations build on an existing and well-calibrated MODFLOW model of the U.S. Northern High Plains aquifer, a hydrologically complex basin under the dual impacts of conversion of native vegetation to intense irrigated agricultural fields and climate change. Simulated groundwater recharge from four different land models are used to drive MODFLOW groundwater simulations. Results show relatively large discrepancies between recharge estimates among simulations. Forcing MODFLOW using recharge simulated by some of the LSMs in place of a simple water balance model marginally improves MODFLOW groundwater simulation. Further, our results support the efficacy of coupling LSMs to a sophisticated groundwater model such as MODFLOW. The coupling results in notable improvements in matching the historical groundwater levels through reduction of the skewness coefficient in percent bias histogram (from 1.50 and 1.41 in original LSMs to 0.44 and 0.27, respectively, when MODFLOW is forced by groundwater recharge from LSMs) and reduction of bias. This modeling effort seeks to identify the best compromise between comprehensive land surface processes from global LSMs and advanced representation of groundwater from regional models.

Assessing Groundwater Recharge in the Wabe River Catchment, Central Ethiopia, through a GIS-Based Distributed Water Balance Model

The utilization of groundwater has emerged as an indispensable asset in facilitating economic advancement, preserving ecological integrity, and responding to the challenges posed by climate change, especially in regions characterized by aridity and semi-aridity. The sustainable management of water resources requires an assessment of the geographical and temporal patterns of groundwater recharge. The present study employed the GIS-based WetSpass-M model to model the water balance components by utilizing hydro-meteorological and biophysical data from the Wabe catchment, which spans an area of 1840 km2 in central Ethiopia, for a long time. The objective of this study was to assess the long-term average annual and seasonal groundwater recharge for the catchment area utilizing the WetSpass-M model. The input data were collected through remote sensing data and surveys in the field. The model was employed to gain insights into the process of groundwater recharge in a particular region and to facilitate effective management, prudent utilization, and sustainable planning of water resources in the long run. Water balance components were estimated using seasonal fluctuations in evapotranspiration, surface runoff, and groundwater recharge. The Wabe catchment’s summer, winter, and mean long-term yearly groundwater recharge were determined to be 125.5 mm, 78.98 mm, and 204.51 mm, respectively. The model indicates that summer seasons account for 86.5% of the mean annual precipitation, while winter seasons account for 13.5%. On the other hand, the groundwater system percolates 14.8% of the total annual rainfall (1374.26 mm). While evapotranspiration accounts for 51% of total precipitation and surface runoff accounts for 34.1%, the Wabe catchment’s mean annual evapotranspiration and surface runoff values are simulated at 701.11 mm and 485.58 mm, respectively. The findings suggest the use of the WetSpass-M model to precisely calculate the water balance components within the Wabe catchment.

GLOBGM v1.0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model

Abstract. We discuss the various performance aspects of parallelizing our transient global-scale groundwater model at 30′′ resolution (30 arcsec; ∼ 1 km at the Equator) on large distributed memory parallel clusters. This model, referred to as GLOBGM, is the successor of our 5′ (5 arcmin; ∼ 10 km at the Equator) PCR-GLOBWB 2 (PCRaster Global Water Balance model) groundwater model, based on MODFLOW having two model layers. The current version of GLOBGM (v1.0) used in this study also has two model layers, is uncalibrated, and uses available 30′′ PCR-GLOBWB data. Increasing the model resolution from 5′ to 30′′ creates challenges, including increased runtime, memory usage, and data storage that exceed the capacity of a single computer. We show that our parallelization tackles these problems with relatively low parallel hardware requirements to meet the needs of users or modelers who do not have exclusive access to hundreds or thousands of nodes within a supercomputer. For our simulation, we use unstructured grids and a prototype version of MODFLOW 6 that we have parallelized using the message-passing interface. We construct independent unstructured grids with a total of 278 million active cells to cancel all redundant sea and land cells, while satisfying all necessary boundary conditions, and distribute them over three continental-scale groundwater models (168 million – Afro–Eurasia; 77 million – the Americas; 16 million – Australia) and one remaining model for the smaller islands (17 million). Each of the four groundwater models is partitioned into multiple non-overlapping submodels that are tightly coupled within the MODFLOW linear solver, where each submodel is uniquely assigned to one processor core, and associated submodel data are written in parallel during the pre-processing, using data tiles. For balancing the parallel workload in advance, we apply the widely used METIS graph partitioner in two ways: it is straightforwardly applied to all (lateral) model grid cells, and it is applied in an area-based manner to HydroBASINS catchments that are assigned to submodels for pre-sorting to a future coupling with surface water. We consider an experiment for simulating the years 1958–2015 with daily time steps and monthly input, including a 20-year spin-up, on the Dutch national supercomputer Snellius. Given that the serial simulation would require ∼ 4.5 months of runtime, we set a hypothetical target of a maximum of 16 h of simulation runtime. We show that 12 nodes (32 cores per node; 384 cores in total) are sufficient to achieve this target, resulting in a speedup of 138 for the largest Afro–Eurasia model when using 7 nodes (224 cores) in parallel. A limited evaluation of the model output using the United States Geological Survey (USGS) National Water Information System (NWIS) head observations for the contiguous United States was conducted. This showed that increasing the resolution from 5′ to 30′′ results in a significant improvement with GLOBGM for the steady-state simulation when compared to the 5′ PCR-GLOBWB groundwater model. However, results for the transient simulation are quite similar, and there is much room for improvement. Monthly and multi-year total terrestrial water storage anomalies derived from the GLOBGM and PCR-GLOBWB models, however, compared favorably with observations from the GRACE satellite. For the next versions of GLOBGM, further improvements require a more detailed (hydro)geological schematization and better information on the locations, depths, and pumping rates of abstraction wells.

Delineation of endorheic drainage basins in the MERIT-Plus dataset for 5 and 15 minute upscaled river networks

The MERIT-Hydro networks re-gridded by the Iterative Hydrography Upscaling (IHU) algorithm do not retain exo- or endorheic basin attributes from the original data. Here we developed methods to assign such attributes to those and any other digital river networks. The motivation is that endorheic inland drainage basins are essential for hydrologic modelling of global and regional water balances, land surface water storage, gravity anomalies, sea level rise, etc. First, we create basin attributes that explicitly label endorheic and exorheic catchments by the criteria of direct or hidden connectivity to the ocean without changing their flow direction grid. In the second step we alter the delineation of endorheic basins by the merging algorithm that eliminates small inland watersheds to the adjacent host basins. The resulting datasets have a significantly reduced number of endorheic basins while preserving the total land portion and topology of the inland basins. The data was validated using the Water Balance Model by comparing volume of endorheic inland depressions with modelled water accumulation in their inland lakes.

Runoff Variability in the Truckee–Carson River Basin from Tree Rings and a Water Balance Model

Abstract Regional warming and associated changes in hydrologic systems pose challenges to water supply management in river basins of the western United States and call for improved understanding of the spatial and temporal variability of runoff. We apply a network of total width, subannual width, and delta blue intensity tree-ring chronologies in combination with a monthly water balance model to identify droughts and their associated precipitation P and temperature T footprints in the Truckee–Carson River basin (TCRB). Stepwise regression gave reasonably accurate reconstructions, from 1688 to 1999, of seasonal P and T (e.g., R2 = 0.50 for May–September T). These were disaggregated to monthly values, which were then routed through a water balance model to generate “indirectly” reconstructed runoff. Reconstructed and observed annual runoff correlate highly (r = 0.80) from 1906 to 1999. The extended runoff record shows that twentieth-century droughts are unmatched in severity in a 300-yr context. Our water balance modeling reconstruction advances the conventional regression-based dendrochronological methods as it allows for multiple hydrologic components (evapotranspiration, snowmelt, etc.) to be evaluated. We found that imposed warming (3° and 6°C) generally exacerbated the runoff deficits in past droughts but that impact could be lessened and sometimes even reversed in some years by compensating factors, including changes in snow regime. Our results underscore the value of combining multiproxy tree-ring data with water balance modeling to place past hydrologic droughts in the context of climate change. Significance Statement We show how water balance modeling in combination with tree-ring data helps place modern droughts in the context of the past few centuries and a warming climate. Seasonal precipitation and temperature were reconstructed from multiproxy tree-ring data for a mountainous location near Lake Tahoe, and these reconstructions were routed through a water balance model to get a record of monthly runoff, snowmelt, and other water balance variables from 1688 to 1999. The resulting extended annual runoff record highlights the unmatched severity of twentieth-century droughts. A warming of 3°C imposed on reconstructed temperature generally exacerbates the runoff anomalies in past droughts, but this effect is sometimes offset by warming-related changes in the snow regime.

Evaluation and comparison of different methods for determining the contribution of climatic factors and direct human interventions in reducing watershed discharge

Planning for reducing climate changes impacts and human interventions on river discharge relies on determining the extent to which factor has contributed to the observed changes. However, the diversity of approaches and methods proposed for assessing the impact of human and climatic factors, coupled with limitations in data and time, necessitate the careful selection of suitable methods. This study aims to address these challenges by providing a reliable framework to reduce uncertainty and select appropriate methods for quantifying the contribution of human and climatic factors to runoff changes using available information. To achieve this goal, a comparative analysis of different approaches and methods was conducted in three stages: trend determination, assessment of homogeneity and breakpoints of the meteorological and hydrological watershed, and quantification of the contribution of climatic and human factors, followed by validation against real evidence. Subsequently, these methods were employed to evaluate the contribution of climatic and human factors in the Boukan watershed, enabling a quantitative comparison of the results. The findings revealed an upward trend in temperature, a downward trend in precipitation and runoff, and significant changes in annual runoff in 1997. The results obtained from various methods exhibited a range of variations, attributing human factors to 35% to 85% of the reduction in runoff, while climatic factors accounted for 15% to 64%. In general, the box plot analysis indicated that human factors contributed approximately 57% on average, whereas climatic factors contributed around an average of 47%. Additionally, the examination of land use changes, resource utilization, and consumption patterns further supported the notion of human factors playing a more substantial role in the regional runoff reduction. Based on the available evidence, the double-mass curve methods, the water balance model, and the SWAT are identified as the most suitable approaches for this watershed, displaying a better fit to reality. Therefore, given the wide range of results, adopting multiple methods with different methodologies becomes crucial to reduce uncertainty. In this context, the proposed framework can serve as a valuable guide for selecting appropriate methods and decision-making processes.

The influence of evaporation and rainfall on the reservoir water balance equation

Evaporation has a major significance in the water balance of a reservoir. Usually, recorded data for the evaporation on the free surface of a reservoir are not available. There are numerous empirical relationships for the assessment of the evaporation that can be implemented into the water balance equation. In this paper, for Vidraru, one of the largest reservoirs in Romania, the Hargreaves method is used to estimate the evaporation values that are compared with recorded data obtained from Meteoblue archive. Recorded precipitation and evaporation data are used in mathematical model for water balance to find the answer to the question: can the evaporation and the directly water surface rainfall be neglected in the monthly/annual water balance of a reservoir? Daily meteorological values for the minimum and maximum temperature, evaporation and precipitation measured in the Vidraru reservoir area are used in this work. The main conclusion of the paper is that although in the summer months, on the surface of the lake, the amount of water lost through the evaporation is greater than the amount of water from the precipitations, on the time horizon of one year, the two components of the water balance of the reservoir have close values. Thus, for an accurate application of the water balance equation for a reservoir, the two variables, evaporation and precipitation, can be both considered or both neglected.