Water Resources Management Planning Research Articles

A disaggregated assessment of national water security: An application to the river basins in Thailand

Achieving water security is a global concern in the age of changing climate, population increase, urbanization, intensive socio-economic development, and land-use change. Addressing water security challenges is most appropriate at the river basin scale since hydrological boundaries at which water flows differ from administrative boundaries, and it can provide policymakers and decision-makers key insights to better support water management practices. This study carries out a disaggregated assessment of national water security by applying an indicator-based framework to evaluate water security conditions in all twenty-five river basins of Thailand from 2007 to 2015. The framework comprises five broad dimensions and eleven indicators. The study results revealed that the overall water security condition in Thai river basins has improved during this period. However, a fine-grained analysis at the dimensions and indicator level of water security shows that water productivity and the watershed health dimension are of concern in most river basins. The agricultural water productivity and the wastewater treatment capacity have deteriorated over the years in most basins. Likewise, it emerged that basins need to enhance their water resource management plans to account for future water challenges. The water security assessment framework presented in this study links well to the plans, policies, visions, and strategies developed for water resource management in Thailand. Thus, it can act as a decision-support tool to monitor the effectiveness of these plans and policies developed and arrive at interventions to enhance Thailand's water security.

Impacts of combined and separate land cover and climate changes on hydrologic responses of Dhidhessa River basin, Ethiopia

ABSTRACT The combined effects of climate and land cover changes influence hydrologic responses of a basin in an offsetting or synergistic manner depending on the nature and severity of the changes. As such, estimating the impacts of these environmental changes on hydrologic responses is crucial for planning water resources management. However, such a comprehensive study is missing in most basins of Ethiopia, particularly in the Dhidhessa River basin (DRB). The aim of this study is, therefore, to quantify the combined and separate impacts of land cover and climate changes on multiple hydrologic variables for the DRB. The Calibrated Soil and Water Analysis Tool (SWAT) model and statistical techniques were integrated for this study. Quantifying the separate and combined effects of land cover and climate changes on multiple hydrologic responses at a local scale, and determining the relative contribution of the changes are the strength of this study. The result indicated better performance of the SWAT model in simulating water balance components for the DRB. Significant changes in hydrologic responses were observed in response to the land cover changes, and the increasing trends of temperature and rainfall observed during the last 30 years in DRB. The result showed increasing actual evapotranspiration (AET), streamflow, and surface runoff while decreasing groundwater recharge. Surface runoff was more affected by land cover change than by climate change, whereas streamflow and AET were more affected by climate change than land cover change during the last 30 years in the basin. The combined effects of land cover and climate changes played an offsetting effect on groundwater recharge and AET. Overall, the simulated hydrologic responses will have negative effects on water resource availability and agricultural production in the basin and the surroundings. Therefore, implementing integrated watershed management strategies, such as soil and water conservation and afforestation, could minimize the negative impact.

Quantifying the uncertainty in future groundwater recharge simulations from regional climate models

AbstractThis study aims to show how future groundwater recharge (GR) simulations in arid areas respond to uncertainty in climatic parameters—a question, if explored, that bridges a gap in water resources management plans. To this aim, eight regional climate models (RCMs) under two representative concentration pathways (RCP4.5 and RCP8.5) projected four climatic parameters [surface air temperature, precipitation, wind speed, and potential evapotranspiration (PET)] over Qatar during the period of 2071–2100. Using topographic and groundwater data, a physically based water balance model was built to simulate future GR under these 16 scenarios. Results show high uncertainty in climatic parameters. Relative to the reference period (1976–2005), values varied under RCP4.5 (RCP8.5) from +1.8 to +3.4 (+3.8 to +5.6)°C for average temperature, −48% to +15% (−60% to +6%) for annual precipitation, −0.23 to +0.1 (−0.27 to +0.04) m/hour for wind speed, and from −5.7 to +12.8 (+4.3 to +17) mm for annual PET. Uncertainty in climatic parameters caused great uncertainty in future GR estimations. During the late 21st century, GR simulations varied from −67% to +64% with an average value of −20% under RCP4.5, and from −81% to +8% with an average value of −36% under RCP8.5. The greatest uncertainty resulted from the driving model, whereas the choice of emission scenario had a secondary impact. Since GR is a critical component of feeding arid aquifers, the study's findings emphasize the importance of both considering the uncertainty associated with climatic parameters and the regional climatic information chosen.

Structure construction, evolution analysis and sustainability evaluation of Water-Ecological-Economic system

Under the influence of human activities, the unary water cycle has been transformed into a “natural–social” dualistic water cycle, and the analysis of driving mechanism of the water system under the dualistic water cycle has become an important proposition for sustainable human-water development. This study explored the connotation, framework, and structure of the Water-Ecological-Economic (WEE) system. The WEE system encompasses water resources, society and economy, water use efficiency, water environment, and water ecology subsystems which interact functionally. And system dynamics is used to drive the evolution of system coupling. For each subsystem's characteristics, its sustainability evaluation index is proposed. MDM-TOPSIS combination evaluation model is applied to calculate the weights of indices and the sustainability comprehensive indicator of WEE system. Taking Nanyang in China as a case study, the results show that the sustainability of the WEE system has a downward trend in the early stage, but in the middle and late stages, ecological and environmental protection is considered, the sustainability level shows an upward trend with the support of several safeguard policies. The WEE system and its sustainability assessment theory proposed in this study will provide scientific support to water resources management and sustainable development planning.

Morphometric characterization and land use of the Pajeú river basin in the Brazilian semi-arid region

The watershed are units controlling hydrological processes and essential for implementation of water resources management policies. The present study aims to integrate the morphometry and land use of the Pajeú river Basin and the Boa Vista micro-basin (headwater of the Pajeú river) using satellite data and a set of remote sensing techniques in open-source software (QGIS). The studied areas are in the semi-arid region of the Pernambuco State, Brazil. Physical morphometric parameters (area, perimeter, axial length, compactness factor, form factor, elongation ratio, and circularity ratio), hydrological parameters (length and distribution of the drainage network, drainage density, hydrographic density, constant of channel maintenance, textural ratio, sinuosity, concentration time, and extension of surface course) and relief (slope and altitude map) were produced. Furthermore, in the micro-basin, we determined the distribution of surface reservoirs using the Modified Normalized Difference Water Index (MNDWI). The Pajeú river basin and the micro-basin have an elongated shape (form factor <0.4 and a capacity coefficient greater than 1.8), approximately 65% of areas with a slope of less than 8%, and moderately developed drainage network; thus, the regions studied are not prone to flooding. However, more than 70% of the basin has soils that have a low infiltration capacity, which, when associated with the conditions of removal of native vegetation, tends to favor the occurrence of floods. Through the integration of land use and morphometry, we found that about 40% of the areas that should be riparian forests are under agricultural activities. A more detailed analysis of the morphometry-coverage-soil-hydrology interactions in watersheds helps understand the hydrological processes and basin management. The presented results can be useful for modeling studies in the basin and for future water resources management plans.

Mapping 20 years of irrigated croplands in China using MODIS and statistics and existing irrigation products

As a routine agricultural practice, irrigation is fundamental to protect crops from water scarcity and ensure food security in China. However, consistent and reliable maps about the spatial distribution and extent of irrigated croplands are still unavailable, impeding water resource management and agricultural planning. Here, we produced annual 500-m irrigated cropland maps across China for 2000–2019, using a two-step strategy that integrated statistics, remote sensing, and existing irrigation products into a hybrid irrigation dataset. First, we generated intermediate irrigation maps (MIrAD-GI) by fusing the MODIS-derived greenness index and statistical data. Second, we collected all existing available irrigation maps over China and integrated them with MIrAD-GI into an improved series of annual irrigation maps, using constrained statistics and a synergy mapping method. The resultant maps had moderate overall accuracies (0.732~0.819) based on nationwide reference ground samples and outperformed existing irrigation products by inter-comparison. As the first of this kind in China, the annual maps delineated the spatiotemporal pattern of irrigated croplands and could contribute to sustainable water use and agricultural development.

Responses of Soybean Water Supply and Requirement to Future Climate Conditions in Heilongjiang Province

Understanding future changes in water supply and requirement under climate change is of great significance for long-term water resource management and agricultural planning. In this study, daily minimum temperature (Tmin), maximum temperature (Tmax), solar radiation (Rad), and precipitation for 26 meteorological stations under RCP4.5 and RCP8.5 of MIRCO5 for the future period 2021–2080 were downscaled by the LARS-WG model, daily average relative humidity (RH) was estimated using the method recommended by FAO-56, and reference crop evapotranspiration (ET0), crop water requirement (ETc), irrigation water requirement (Ir), effective precipitation (Pe), and coupling degree of ETc and Pe (CD) for soybean during the growth period were calculated by the CROPWAT model in Heilongjiang Province, China. The spatial and temporal distribution of these variables and meteorological factors were analyzed, and the response of soybean water supply and requirement to climate change was explored. The result showed that the average Tmin, Tmax, and Rad under RCP4.5 and RCP8.5 increased by 0.2656 and 0.5368 °C, 0.3509 and 0.5897 °C, and 0.0830 and 0.0465 MJ/m², respectively, while the average RH decreased by 0.0920% and 0.0870% per decade from 2021 to 2080. The annual average ET0, ETc, Pe, and Ir under RCP4.5 for 2021–2080 were 542.89, 414.35, 354.10, and 102.44 mm, respectively, and they increased by 1.92%, 1.64%, 2.33%, and −2.12% under the RCP8.5, respectively. The ranges of CD under RCP4.5 and RCP8.5 were 0.66–0.95 and 0.66–0.96, respectively, with an average value of 0.84 for 2021–2080. Spatially, the CD showed a general trend of increasing first and then decreasing from west to east. In addition, ET0, ETc, and Pe increased by 9.55, 7.16, and 8.77 mm per decade, respectively, under RCP8.5, while Ir decreased by 0.65 mm per decade. Under RCP4.5 and RCP8.5, ETc, Pe, and Ir showed an overall increasing trend from 2021 to 2080. This study provides a basis for water resources management policy in Heilongjiang Province, China.

Precipitation Trends Analysis Using Gridded Dynamic Sampling Zones: Case Study Yangtze Delta Megalopolis

As a result of the fast growth of remote sensing and data assimilation technology, many global land use land cover (LULC) and climate reanalysis data sets have been used to advance our understanding of climate and environmental change. This paper investigates the precipitation variations of the Yangtze Delta Megalopolis by using precipitation reanalysis data under conditions of dynamic urban sprawl. Compared with current precipitation characteristic analyses, which are often based on a limited number of ground rainfall stations, the approach followed in this study comprises a grid-based statistical method using large sets of samples with a uniform distribution and a same representative grid area. This novel approach of dynamic sampling is applied in this study to overcome the temporal and spatial inconsistency of stationary sampling. This approach allows to examine the impact of urbanization on regional precipitation characteristics. The Yangtze Delta Megalopolis (YDM) region, one of the most developed regions in China, was selected as a case study to evaluate the impact of urbanization on subsequent precipitation features. The results reveal that the annual total precipitation (TP) and the maximum daily precipitation (MDP) in both urban and non-urban areas of the YDM region generally have increased during the past 30 years. Hence, the region has become increasingly humid. Extrema of annual MDP and TP show obvious spatial characteristics, in which most maxima are located in the southern part of YDM while minima are more concentrated in the northern part. This newly developed approach has potentials for application in studies where underlying surface features exhibit rapid alterations. The findings of this case study provide relevant information for planning and design of regional water resources management, flood risk management, and planning of the urban drainage system of the YDM region.

Promotion of environmental projects to conform with UWWTD and integrated water management

Abstract The region of East Attica in Greece faces stress on its water supply, caused mainly by agricultural activities and tourism in the summer. It is therefore imperative for the region to integrate water reuse in its water resources management plan. To this end, a project was conceived that accommodated stakeholder management practices to ensure public acceptance with the challenge to transform potential project risks to opportunities. In particular, two major wastewater projects in the region were approved for co-financing by the European Union (EU) Cohesion funds and implementation by the Athens Water Supply and Sewerage Company (EYDAP S.A.) for agglomerations in East Attica (Rafina/Artemida &amp; Marathon agglomerations). Both projects aim to achieving compliance with 91/271/E.E.C, Urban Wastewater Treatment Directive (UWWTD) and producing treated effluent wastewater that complies with the national standards for unlimited irrigation and urban reuse. Furthermore, another wastewater scheme, co-financed by EU funds with the beneficiary being the Prefecture of Attica, involves the agglomerations of Koropi and Paiania respectively, which are also currently non-compliant. The aforementioned scheme is presently under development after upgrading with advanced tertiary treatment will also produce quantity of reclaimed water suitable for aquifer recharge to restore the water quality of groundwater bodies.

Projections of precipitation change from CMIP6 based on a new downscaling method in the Poyang Lake basin, China

Study regionThe Poyang Lake (PL) basin, located in the middle and lower reaches of the Yangtze River, China. Study focusThis study investigated the future precipitation variations during 2020–2100 under four shared socioeconomic pathways (SSPs) by downscaling the CMIP6 outputs using a new scale-based downscaling method, which integrated the GWR-KED method and time transfer matrices by linking the precipitation in the historical and future periods. New hydrological insightsCompared with the original CMIP6 outputs, the downscaled precipitation predictions exhibited large improvements, with mean absolute errors (MAEs) improved by a range of 37.49~66.81% and 74.95~75.38% on the seasonal and annual scale, respectively. The downscaled projections showed that the basin would be wetter at the annual scale during the next 80 years. Precipitation in spring would be increase over the entire basin under all future scenarios except SSP1–2.6. Parts of the PL basin exhibit drier trends under the four scenarios in summer, with the largest drying area occurring in the SSP2–4.5 scenario. Except in the SSP2–4.5 scenario, precipitation in autumn has increasing trends in all scenarios across the PL basin. Precipitation in winter shows a drying trend in some areas except in the SSP1–2.6 scenario, with the largest area occurring in SSP5–8.5. The results provide improved precipitation information for policy-making in water resource management and adaptation planning to mitigate Yangtze River floods in the future.

Capability and Robustness of Novel Hybridized Artificial Intelligence Technique for Sediment Yield Modeling in Godavari River, India

Suspended sediment yield (SSY) prediction plays a crucial role in the planning of water resource management and design. Accurate sediment prediction using conventional models is very difficult due to many complex processes. We developed a fully automatic highly generalized accurate and robust artificial intelligence models for SSY prediction in Godavari River Basin, India. The genetic algorithm (GA), hybridized with an artificial neural network (ANN) (GA-ANN), is a suitable artificial intelligence model for SSY prediction. The GA is used to concurrently optimize all ANN’s parameters. The GA-ANN was developed using daily water discharge, with water level as the input data to estimate the daily SSY at Polavaram, which is the farthest gauging station in the downstream of the Godavari River Basin. The performances of the GA-ANN model were evaluated by comparing with ANN, sediment rating curve (SRC) and multiple linear regression (MLR) models. It is observed that the GA-ANN contains the highest correlation coefficient (0.927) and lowest root mean square error (0.053) along with lowest biased (0.020) values among all the comparative models. The GA-ANN model is the most suitable substitute over traditional models for SSY prediction. The hybrid GA-ANN can be recommended for estimating the SSY due to comparatively superior performance and simplicity of applications.

Impact of climate change on future precipitation amounts, seasonal distribution, and streamflow in the Omo-Gibe basin, Ethiopia

This study projected the impact of climate change on the amount of precipitation, seasonal distribution, and streamflow of the Omo-gibe basin, Ethiopia. Projections of climate change using the results of high-resolution multimodal ensembles from fifteen regional climate models (RCMs) of the Coordinated Regional Climate Reduction Experiment (CORDEX)-Africa were statistically downscaled and bias-adjusted using a quantile mapping approach. Precipitation and temperature were projected under RCP 8.5 and RCP 4.5 emission scenarios. Climate and streamflow projections from a mean ensemble of RCMs in the near future (2025–2050), medium future (2051–2075), and far future (2076–2100) were compared to the reference (1989–2019). Mann-Kendall (MK) trend testing was used to determine if a change is statistically significant and to detect trends in temperature, precipitation, and streamflow. The Soil and Water Assessment Tool (SWAT) hydrological model was used to project the impact of climate change on the streamflow. According to RCP4.5 and RCP8.5, the emission scenarios predicted significant positive (rising) temperature, but significant negative (decreasing) precipitation and streamflow. The average temperature projected increases range from 2.40-3.34 °C under the RCP 4.5 emission scenarios and 2.6–4.54 °C under the RCP 8.5 emission scenarios. Annual average precipitation projected decreases range between 10.77-13.11% under the RCP 4.5 emission scenario, while the RCP 8.5 emission scenarios decrease range between 11.10-13.86% in the rainy summer season (June–August) and the irregular rain season (March–May). Projected annual average streamflow decrease range between 7.08-10.99% under the RCP 4.5 emission scenarios and 10.98–12.88% under the RCP 8.5 emission scenarios. Results on projected temperature increases and reductions in precipitation and streamflow will help to develop effective adaptation measures to reduce the ongoing impacts of climate change and draw up long-term water resource management plans in the river basin. Both the results and the multidisciplinary approach will be vital to irrigation and hydropower project planners.

Virtuous Cycle: An Idea of Water Resources Management and Top-Level Planning

Facing the conflict between human activities and the ecological environment, this study proposes a “Virtuous Cycle” concept of water resource management and top-level planning. By analyzing and summarizing typical experiences from both macro-policy and micro-practice, the characteristics and mechanisms of the Virtuous Cycle are discussed. According to the analysis method of “Problem-Attribution-Goal-Task-Measures” (PAGTM), taking the “Five Water Governance” water management project in Zhejiang Province of China as a case study, the specific measures and technical framework of the Virtuous Cycle are explored. This study hopes to provide a reference for the top-level planning and path design of harmonious and sustainable natural-social water resources management.

Assessing Xeriscaping as a Retrofit Sustainable Water Consumption Approach for a Desert University Campus

Assessing water usage associated with urban green infrastructure is crucial for water resource management and sustainable planning of desert campus areas. A public university campus layout in the desert region is considered an urban city subject to urban water consumption (UWC) of significant intensity and extent, even though the urban layout is essential to all campus occupants’ comfort and environmental sustainability needs. Hence, there is a need to reduce its detrimental effects through sustainable methods for campus water content. This study focuses on assessing urban xeriscaping landscape quantities as a practical potential approach to support university campus decision-makers in reducing urban water consumption and preserving the urban campus water content as asset management and life quality. Four selected landscape field experiments were undertaken by adopting xeriscaping landscape design instead of existing conventional urban design at King Faisal University’s (KFU) campus layout, Al-Ahsaa, Eastern Province, Saudi Arabia. The study built a specific practical sustainability retrofit approach in water conservation from conventional to xeriscaping method inside the existing public desert campus area. Applying the study approach framework considering xeriscaping layout design provided sustainability requirements, retrofit approach, and pathway to effective landscape mapping, based on reasonable and accurate quantities of xeriscaping landscape items, to convert the KFU campus layout as a low water consumption campus with an average reduction of 41% water consumption within the remaining campus layout. The results of this study contribute to the water conservation and management in university desert campus and opens the door for other studies on the use of this approach for thermal reduction, economic and environmental benefits beside its value for water reduction.

Cluster and Trend Analysis of Rainfall Time Series in the Nakdong River Basin

In Korea, it is difficult to efficiently manage water resources, due to the variability of rainfall in addition to the increasing outflow due to climate change in recent years. Therefore, if the trends and characteristics of rainfall at each station can be identified in advance, the problems caused by the variability of rainfall can be effectively dealt with. In this study, the data on rainfall characteristics of 64 rainfall stations in the Nakdong river basin were collected for the period 2000 to 2019. The data were analyzed according to the elevation of each station using K-means cluster analysis, and the rainfall trends at each station were identified by homogeneity test and modified Mann-Kendall test. The analysis showed an increasing trend in March, April, November, December, spring and autumn, and a decreasing trend in January, May, September, summer and year. Also, based on the cluster analysis, it was confirmed that when the number of clusters was set to three, the rainfall characteristics were different depending on the elevation of each station. It is believed that linking the characteristics of rainfall by cluster and the results of trend analysis by station derived from the study can be used to come up with a water resource management plan that takes into account the variability of rainfall.

Assessing the Impact of the Farakka Barrage on Hydrological Alteration in the Padma River with Future Insight

Climate change and human interventions (e.g., massive barrages, dams, sand mining, and sluice gates) in the Ganga–Padma River (India and Bangladesh) have escalated in recent decades, disrupting the natural flow regime and habitat. This study employed innovative trend analysis (ITA), range of variability approach (RVA), and continuous wavelet analysis (CWA) to quantify the past to future hydrological change in the river because of the building of the Farakka Barrage (FB). We also forecast flow regimes using unique hybrid machine learning techniques based on particle swarm optimization (PSO). The ITA findings revealed that the average discharge trended substantially negatively throughout the dry season (January–May). However, the RVA analysis showed that average discharge was lower than environmental flows. The CWA indicated that the FB has a significant influence on the periodicity of the streamflow regime. PSO-Reduced Error Pruning Tree (REPTree) was the best fit for average discharge prediction (RMSE = 0.14), PSO-random forest (RF) was the best match for maximum discharge (RMSE = 0.3), and PSO-M5P (RMSE = 0.18) was better for the lowest discharge prediction. Furthermore, the basin’s discharge has reduced over time, concerning the riparian environment. This research describes the measurement of hydrological change and forecasts the discharge for upcoming days, which might be valuable in developing sustainable water resource management plans in this location.

An interval two-stage fuzzy fractional programming model for planning water resources management in the coastal region – A case study of Shenzhen, China

In this study, an interval two-stage fuzzy fractional programming (TFFP) method is developed to facilitate collaborative governance of economy and water resources. Methods of interval programming, fuzzy programming, two-stage programming, and fractional programming are integrated within a general system optimization framework. The main contribution of TFFP is simultaneously addressing various uncertainties and tackling trade-offs between environmental and economic objectives in the optimized schemes for water resources allocation. A case study of a highly urbanized coastal city (i.e., Shenzhen) in China is provided as an example for demonstrating the proposed approach. According to the results, industrial sectors should receive 34.8% of total water supply, while agricultural sectors should receive 1.5%. For the spatial allocation of water resources, Bao An, Long Gang, and Fu Tian districts should be allocated 21.6%, 20.5%, and 14.8% water to promote the economic development. The discharge analysis indicates that chemical oxygen demand (CODcr) and total phosphorus (TP) would be key pollutants. Moreover, the optimized seawater desalination volume would be negligibly influenced by price, while the upper bounds of desalination would be increased with the raising acceptable credibility levels in the period of 2031–2035. Analysis of desalination prices also reveals that the decision-makers should increase the scale of desalination in the period of 2021–2025. In addition, the effectiveness and applicability of TFFP would be evaluated under economic maximization scenarios. The result showed that the economic maximization scenario could obtain higher economic benefits, but it would be accompanied by a larger number of pollutant discharges. It is expected that this study will provide solid bases for planning water resources management systems in coastal regions.

Assessment of wavelet-SVR and wavelet-GP models in predicting the groundwater level using areal precipitation and consumption data

ABSTRACT Assessing and predicting groundwater level (GWL) fluctuations using specific models provides valuable information for water resources management and consumption planning. In this study, areal monthly data of GWL precipitation and consumptions were used to predict the GWL using genetic programming (GP), wavelet-GP, support vector regression (SVR) and wavelet-SVR models over a period of 11 years. Appropriate time lags were determined using the autocorrelation function (ACF) and cross-correlation function (CCF). It was found that consumption with a two-month lag and precipitation with a one-month lag have the greatest effect on the GWL. Discrete wavelet transform (DWT) was used to decompose time series into low- and high-frequency components for wavelet-SVR and wavelet-GP models. Two types of input structures were used for modelling (single GWL data and GWL considering consumptions and precipitation data). The results showed that the wavelet-SVR model had the best performance (according to R, RMSE and NSE) compared to the other three models, and SVR had better performance than the GP.

Estimating Reservoir Inflow and Outflow From Water Level Observations Using Expert Knowledge: Dealing With an Ill‐Posed Water Balance Equation in Reservoir Management

AbstractQuantifying reservoir water balance is an essential process for the efficient management of water resources. Water level records are often the only data available for reservoir analysis, which causes an ill‐posed problem in water resource system planning. This study proposes an analytical framework to estimate reservoir inflow and outflow from water level observations using hydrological models and reasoning carefully derived from expert knowledge and soft data. Partial reservoir inflow hydrographs were constructed from water level observations using a continuity equation and knowledge‐based constraints developed for periods of no spillway discharge. A bucket‐type rainfall‐runoff model was then calibrated to the partial inflow hydrographs. Finally, a complete reservoir inflow hydrograph was constructed using the calibrated models, which were then employed to estimate detailed reservoir outflow components under a full water balance relationship between inflow, outflow, water levels, and reservoir operation rules. The proposed solution for the ill‐posed water balance equation outperformed conventional (benchmark) approaches in accuracy and uncertainty in its application to agricultural reservoirs. This study demonstrates how hydrological modeling and reasoning, which are discreetly designed based on expert knowledge, can help to solve the ill‐posed water balance equation by creating supplementary information regarding the problem. The proposed framework is expected to assist in reconstructing reservoir routing processes using water level observations for hydrological analysis and water resource management planning.

Evaluation and projection of precipitation in Pakistan using the Coupled Model Intercomparison Project Phase 6 model simulations

AbstractThis study aimed to evaluate the performance of global climate models (GCMs) from the family of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in the historical simulation of precipitation and select the best performing GCMs for future projection of precipitation in Pakistan under multiple shared socioeconomic pathways (SSPs). The spatiotemporal performance of GCMs was evaluated against the Climate Research Unit (CRU) data in simulating annual precipitation during 1951–2014, using the Taylor diagram and interannual variability skill (IVS). Moreover, the modified Mann–Kendall (mMK) and Sen's slope estimator (SSE) tests were employed to estimate significant trends in future precipitation for the period 2015–2100. Based on the comprehensive ranking index (CRI), the HadGEM3‐GC31‐MM model has the highest skill in simulating precipitation distributions followed by EC‐Earth3‐Veg‐LR, CNRM‐ESM2‐1, MPI‐ESM1‐2‐HR, CNRM‐CM6‐1, MRI‐ESM2‐0, CNRM‐CM6‐1‐HR, EC‐Earth3‐Veg, MCM‐UA‐1‐0, INM‐CM5‐0, KACE‐1‐0‐G, CAMS‐CSM1‐0, and HadGEM3‐GC31‐LL models. Furthermore, the projections of the best models ensemble mean (BMEM) showed that the study region will experience a substantial increase in precipitation under SSP3‐7.0 and SSP5‐8.5 but an indolent rise under SSP1‐2.6 and SSP2‐4.5 scenarios. The summer and annual precipitations exhibit a statistically significant increasing trend relative to the winter season under most scenarios. Moreover, the magnitude of monotonic trends in seasonal and annual precipitation progresses from low forcing scenario (SSP1‐2.6) to high forcing scenario (SSP5‐8.5). The findings of the study could provide a benchmark in selecting appropriate GCMs for future projection over a data scare region, like Pakistan. Moreover, the projected trends of future precipitation are crucial in devising adaption and mitigation actions towards sustainable planning of water resource management, food security, and disaster risk management.