Hydrological response of Chamelia watershed in Mahakali Basin to climate change

Groundwater levels and resiliency mapping under land cover and climate change scenarios: a case study of Chitravathi basin in Southern India

Chitravathi basin in India is facing significant challenges as its groundwater resources are facing the impact of land cover and climate change. This study explores the impact of land cover and climate change on groundwater levels and groundwater recharge in the basin using CMIP6 GCMs climate projections data. Taylor Skill Score (TSS) and Rating Metric (RM) were used to rank the GCMs. The top four ranked GCMs, i.e., MPI-ESM1-2-LR, EC-Earth3, MPI-ESM1-2-HR, and INM-CM5-0 were found to produce the most accurate projections under scenarios SSP2-4.5 and SSP5-8.5. Cellular Automata-Artificial Neural Network (CA-ANN) was used to develop future LULC maps. SWAT model was applied for estimating the future groundwater recharge and was calibrated and validated for discharge data, giving the values of R2 = 0.84 and 0.82 and NSE = 0.81 and 0.80 during calibration and validation, respectively. A steady-state groundwater flow model, MODFLOW, was employed to estimate future groundwater levels. Based on the projected groundwater recharge and levels, a resiliency map of the basin was developed. The results indicated that by 2060, under SSP2-4.5 scenario, groundwater levels in the basin would decrease by 54 m, while under the SSP5-8.5 scenario, the decrease would be 62 m. The groundwater resiliency for both SSPs would be poor in 2060. This research will help design and implement adaptation measures to mitigate the impacts of land cover and climate change on Chitravathi basin's groundwater resources. These findings will help to protect and preserve the basin's groundwater supplies.

Implementing conjunctive management of water resources for irrigation development: A framework applied to the Southern Plain of Western Nepal

Climate variability and insufficient irrigation are primary constraints to stable and higher agricultural productivity and food security in Nepal. Agriculture is the largest global freshwater user, and integration of surface- and ground-water use is frequently presented as an strategy for increasing efficiency as well as climate change adaptation. However, conjunctive management (CM) planning often ignores demand-side requirements and a broader set of sustainable development considerations, including ecosystem health and economics of different development strategies. While there is generic understanding of conjunctive use, detailed technical knowhow to realize the CM is lacking in Nepal. This article presents a holistic framework through literature reviews, stakeholders consultations and expert interviews for assessing CM and implementation prospects from a systems-level perspective. We demonstrate the framework through a case study in Western Nepal, where climatic variability and a lack of irrigation are key impediments to increased agricultural productivity and sustainable development. Results show that knowledge of water resources availability is good and that of water demand low in the Western Terai. Additional and coordinated investments are required to improve knowledge gaps as well as access to irrigation. There is therefore a need to assess water resources availability, water access, use and productivity, to fill the knowledge gaps in order to pave pathways for CM. This paper also discusses some strategies to translate prospects of conjunctive management into implementation.

An assessment of climate change impacts on water sufficiency: The case of Extended East Rapti watershed, Nepal

An understanding of water sufficiency provides a basis for informed-planning, development and management of water resources. This study assessed spatio-temporal distribution in water sufficiency in the Extended East Rapti watershed in Nepal. The "Palika" (local government unit) is considered as a spatial-scale and seasons and future periods as temporal-scale. The water sufficiency was evaluated based on water sufficiency ratio (WSR) and water stress index (WSI). A hydrological model was developed to simulate water availability. An ensemble of multiple Regional Climate Models was used for assessing climate change impacts. Results showed water sufficiency by mid-century is projected to decrease; WSR by 40% and WSI by 61%. Despite projected decrease in water sufficiency, annually available water resources are projected as sufficient for the demands until the mid-century, however, seasonal variability and scarcity in future is projected in most Palikas. Such results are useful for water security planning in the Palikas.

Resolution Dependence of Regional Hydro-Climatic Projection: A Case-Study for the Johor River Basin, Malaysia

High resolution models from the High-Resolution Model Intercomparison Project (HighResMIP), part of CMIP6, have the capacity to allow a better representation of the climate system in tropical regions, but how different model resolutions affect hydrological outputs remains unclear. This research aims to evaluate projections of hydro-climatic change of the Johor River Basin (JRB) in southern Peninsular Malaysia between 1985 to 2015 and 2021 to 2050, focusing on uncertainty quantification of hydrological outputs from low (>1°), medium (0.5° to 1°) and high (≤0.5°) horizontal resolution models. These projections show future increases in annual precipitation of 0.4 to 3.1%, minimum and maximum temperature increases of 0.8 to 0.9 °C and 0.9 to 1.1 °C, respectively. These projected climate changes lead to increases in annual mean streamflow of 0.9% to 7.0% and surface runoff of 7.0% to 20.6% in the JRB. These annual mean changes are consistent with those during the wet period (November to December), e.g., streamflow increases of 4.9% to 10.8% and surface runoff of 28.8 to 39.9% in December. Disagreement in the direction of change is found during the dry seasons, (February to March and May to September), where high resolution models project a decrease in future monthly precipitation and streamflow, whilst increases are projected by the medium- and low-resolution models.

Nonlinear recurrence quantification of the monsoon-season heavy rainy-days over northwest Himalaya for the baseline and future periods

Indian summer monsoon has the characteristics of nonlinear dynamical systems. This study verifies the hypothesis that monsoon-season heavy rainy-day climatology over northwest Himalaya would exhibit certain degree of determinism, and expected to modify in its future state due to warming. Hence, recurrence quantification analysis (RQA) leading to quantification of recurrence rate (RR) and determinism (DET) are used. The monsoon-season heavy rainy-day climatologies are computed by area averaging heavy rainy-day (i.e. any day having rainfall ≥35.5 mm) of northwestern Indian Himalaya of Uttarakhand (UK), Himachal Pradesh (HP), and Union Territory of Jammu, Kashmir and Ladakh (JKL). Nonlinear characteristics are identified for a baseline period of 1970-2005 using APHRODITE data, and a bias corrected ensemble data for the future period of 2041-2099 produced using five CORDEX experiments under two warming scenarios, RCP 4.5 and 8.5. The heavy rainy-day climatology during 1970-2005 is having a correlation dimension of 1.5 indicating fractal geometry of the system in phase space. Similarly, occurrences of diagonal lines in the recurrence plots of baseline period over JKL, HP, and UK indicated the system is governed by a nonlinear chaotic attractor. A higher recurrence rate during 1970-2005 over HP (RR = 0.123, DET = 0.83) indicated greater determinism than JKL (RR = 0.119, DET = 0.78) and UK (RR = 0.121, DET = 0.75). Mean prediction time of the nonlinear dynamical trajectories controlling heavy rainy-day climatology of 1970-2005 is noted to be higher over UK. Furthermore, the RQA patterns under warmer climates of RCP 4.5 and 8.5 during 2041-2099 over UK and JKL indicate gradual reduction in the deterministic structures in the phase space. Therefore, it can be inferred that the nonlinear dynamical system governing the monsoon-season heavy rainy-day climatology is expected to lose determinism over certain regions of northwestern Himalaya under warmer climates of RCP 4.5 and 8.5.

Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part I: Model Development)

The soil and water assessment tool (SWAT) hydrological model has been used extensively by the scientific community to simulate varying hydro-climatic conditions and geo-physical environment. This study used SWAT to characterize the rainfall-runoff behaviour of a complex mountainous basin, the Budhigandaki River Basin (BRB), in central Nepal. The specific objectives of this research were to: (i) assess the applicability of SWAT model in data scarce and complex mountainous river basin using well-established performance indicators; and (ii) generate spatially distributed flows and evaluate the water balance at the sub-basin level. The BRB was discretised into 16 sub-basins and 344 hydrological response units (HRUs) and calibration and validation was carried out at Arughat using daily flow data of 20 years and 10 years, respectively. Moreover, this study carried out additional validation at three supplementary points at which the study team collected primary river flow data. Four statistical indicators: Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), ratio of the root mean square error to the standard deviation of measured data (RSR) and Kling Gupta efficiency (KGE) have been used for the model evaluation. Calibration and validation results rank the model performance as “very good”. This study estimated the mean annual flow at BRB outlet to be 240 m3/s and annual precipitation 1528 mm with distinct seasonal variability. Snowmelt contributes 20% of the total flow at the basin outlet during the pre-monsoon and 8% in the post monsoon period. The 90%, 40% and 10% exceedance flows were calculated to be 39, 126 and 453 m3/s respectively. This study provides additional evidence to the SWAT diaspora of its applicability to simulate the rainfall-runoff characteristics of such a complex mountainous catchment. The findings will be useful for hydrologists and planners in general to utilize the available water rationally in the times to come and particularly, to harness the hydroelectric potential of the basin.

Climate change impacts on contaminant loads delivered with sediment yields from different land use types in a Carpathian basin

Soil runoff and sediment transport are considered as an important vector for particle-bound contaminant transfer from source to receiving waters. Under changing climate conditions and rapid basin development, identification of sediment origins is critical for planning further action to reduce erosion effects, and further pollution to surface waters. The goal of this study was to distinguish sediment sources in a Carpathian basin (Wolnica River, southern Poland) and to perform source-oriented contaminant load estimations. Sediment yields (SYLD) and land use specific sediment yields (LUSY) were modeled with the use of the Macromodel DNS/SWAT (Discharge-Nutrients-Sea/Soil and Water Assessment Tool). Sorting of sediment sources was performed by the fingerprinting method using variability of the geochemical composition of soils (Pb, Zn, Cd, Cu, Mn, Ni, Fe, Hg, total N and P, Σ16 PAHs, and 137Cs) of four land use (LU) types: arable lands (A), grasslands (G), residential areas (R), and forests (F). Statistical analysis revealed six metals (Pb, Zn, Cd, Cu, Ni, and Hg) as fingerprint properties providing the best source discrimination in this basin. The contribution of particular land use origin assessed with the use of the mixing model varied in the range of 20-30%. Finally, estimation of land use specific contaminant loads in suspended sediments was performed as a result of a modeling and sediment fingerprinting combination. The final estimates revealed yearly LUSY values varying between 716 t/y for A, 12 t/y for F, and metal loads from 31 kg/y for Zn to values below 100 g/y for Cd and Hg. Long-term predictions (2046-2055) of the metal loads revealed an increase by 75% under the combined RCP 8.5 climate change and land use scenarios. These findings are of great value for land management in the Carpathian basins, especially with regards to the predicted increase of forest cover which significantly alters contaminant signals conveyed through the system.

Inflow Forecast of Iranamadu Reservoir, Sri Lanka, under Projected Climate Scenarios Using Artificial Neural Networks

Prediction of water resources for future years takes much attention from the water resources planners and relevant authorities. However, traditional computational models like hydrologic models need many data about the catchment itself. Sometimes these important data on catchments are not available due to many reasons. Therefore, artificial neural networks (ANNs) are useful soft computing tools in predicting real-world scenarios, such as forecasting future water availability from a catchment, in the absence of intensive data, which are required for modeling practices in the context of hydrology. These ANNs are capable of building relationships to nonlinear real-world problems using available data and then to use that built relationship to forecast future needs. Even though Sri Lanka has an extensive usage of water resources for many activities, including drinking water supply, irrigation, hydropower development, navigation, and many other recreational purposes, forecasting studies for water resources are not being carried out. Therefore, there is a significant gap in forecasting water availability and water needs in the context of Sri Lanka. Thus, this paper presents an artificial neural network model to forecast the inflows of one of the most important reservoirs in northern Sri Lanka using the upstream catchment’s rainfall. Future rainfall data are extracted using regional climate models for the years 2021–2050 and the inflows of the reservoir are forecasted using the validated neural network model. Several training algorithms including Levenberg–Marquardt (LM), BFGS quasi-Newton (BFG), scaled conjugate gradient (SCG) have been used to find the best fitting training algorithm to the prediction process of the inflows against the measured inflows. Results revealed that the LM training algorithm outperforms the other tests algorithm in developing the prediction model. In addition, the forecasted results using the projected climate scenarios clearly showcase the benefit of using the forecasting model in solving future water resource management to avoid or to minimize future water scarcity. Therefore, the validated model can effectively be used for proper planning of the proposed drinking water supply scheme to the nearby urban city, Jaffna in northern Sri Lanka.

Modelling the impact of past and future climate scenarios on streamflow in a highly mountainous watershed: A case study in the West Seti River Basin, Nepal

Hydrological model parameters are important during representation of the hydrological characteristics of a watershed. The West Seti River Basin (WSRB), a prominent Himalayan Basin of Nepal, is a major source of fresh water in the western region of the country. We used the Soil and Water Assessment Tool (SWAT) for hydrological modelling and identified the most sensitive hydrological parameters, while the Sequential Uncertainty Fitting (SUFI-2) technique was employed for model calibration. The model was calibrated for the study period (1999-2005) with a three-year warm-up period (1996-1998). Subsequently, it was validated for three years (2006-2008). The results show that the large number of Hydrological Response Units (HRUs) for model simulation took a considerable time, without improving the performance statistics. Importantly, significant improvements were observed during both calibration and validation periods when elevation bands (EBs) were taken into consideration. The p-factor, r-factor, coefficient of determination (R²), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), Root mean square error (RMSE)-observations, and standard deviation (STDEV) ratio (RSR) were used to measure the performance between observed and simulated values. The values of p-factor, r-factor, R², NSE, PBIAS, and RSR during the calibration were 0.82, 0.80, 0.84, 0.82, 7.2, and 0.42, respectively, whereas during validation they were 0.79, 0.72, 0.83, 0.82, 11.8, and 0.42, respectively. The calibrated model was then used to assess the anticipated river discharge. This study used four regional climate models (RCMs) for precipitation and six for temperature, together with their arithmetical average as multi-model ensembles (MMEs) under two representative concentration pathways (RCPs). We analysed the changes in precipitation, temperature, and river discharge for three future time frames: Future1 (F1: 2020-2044), Future2 (F2: 2045-2069), and Future3 (F3: 2075-2099) with respect to the baseline (1996-2005). The magnitude of changes varied according to the different climate models and warming scenarios. In general, the MMEs showed slightly increasing precipitation (higher during the F2 period), significantly increasing temperature (continuous rising trend), and moderately increasing river discharge (higher during the F2 period). Information such as the anticipated shift in the flow duration curve may be helpful to stakeholders across different water sectors for effective water resource management in the future. From the modelling perspective, the results show greater significance for EBs than HRUs during the modelling of high mountain basins with SWAT. This take-home message would be useful to hydrologists and other stakeholders in evaluating different scenarios over a short duration, without iteratively spending higher computational time.

Modeling the future impacts of climate change on water availability in the Karnali River Basin of Nepal Himalaya

It's unequivocal that the global climate is changing, including the rise in atmospheric temperature and variability in amount and pattern of precipitation, and the rate of temperature change in the Himalayan region is higher than the global average. Since precipitation and temperature are the major driving factors of water resources in the Himalayas both upstream and downstream regions, it is important to understand theimpacts of climate change in water resource availability in the future. In this study, we analyzed the historical hydro-climate data and developed a suitable ensemble of the Coordinated Regional Downscaling Experiment (CORDEX) climate models for the Karnali River Basin (KRB) in western Nepal and assessed the future water availability in different climate scenarios using a semi-distributed catchment scale hydrological model the Soil and Water Assessment Tool (SWAT). The climate data analysis shows that the atmospheric temperature is rising throughout the basin but there is high spatial variability in precipitation trend. The historical river discharge data analysis do not show any significant trend, however, there is some inter-annual variability. Future projection shows that the annual precipitation amount will increase compared to the baseline so does the river discharge. However, this increase is not uniform for all seasons. The post-monsoon season having the lowest observed precipitation will get lesser amount of precipitation in the future and the river discharge also follows the same trend. These anomalies play a crucial role in determining the future water availability for agriculture, hydropower, ecosystem functioning and its services availability to the people living in the KRB as well as in the downstream region.

Climate and landscape mediate patterns of low lentil productivity in Nepal

Lentil (Lens culinaris Medik.) is a cool-season pulse grown in winter cropping cycle in South Asia and provides a major source of nutrition for many low-income households. Lentil productivity is perceived to be sensitive to high rainfall, but few studies document spatial and temporal patterns of yield variation across climate, soil, and agronomic gradients. Using farm survey data from Nepal, this study characterizes patterns of lentil productivity and efficiency for two cropping seasons. Additional insights were derived from on-farm trials conducted over a 5-year period that assess agronomic, drainage, and cultivar interventions. To contextualize the inferences derived from farm surveys and trials, the Stempedia model was used to simulate the severity of Stemphylium blight (Stemphylium botryosum) risk-the principal fungal disease in lentil-with 30 years of historical climate data. Although development efforts in Nepal have prioritized pulse intensification, results confirm that lentil remains a risky enterprise highlighting the prevalence of crop failures (16%), modest yields (353 kg ha-1), and low levels of profitability (US$ 33 ha-1) in wet winters. Nevertheless, site factors such as drainage class influence responses with upland sites performing well in wet winters and lowland sites performing well in dry winters. In wet winters, a phenomena perceived to be increasing, 76% of surveyed farmers reported significant disease pressure and simulations with Stempedia predict that conditions favoring Stemphylium occur in >60% of all years. Nevertheless, simulation results also suggest that these risks can be addressed through earlier planting. Based on the combined results, gains in yield, yield stability, and technical efficiency can be enhanced in western Nepal by: 1) ensuring timely lentil planting to mitigate climate-mediated disease risk, 2) evaluating new lentil lines that may provide enhanced resistance to diseases and waterlogging, and 3) encouraging the emergence of mechanization solutions to overcome labor bottlenecks.

Mapping groundwater resiliency under climate change scenarios: A case study of Kathmandu Valley, Nepal

Groundwater resources of Kathmandu Valley in Nepal are under immense pressure from multiple stresses, including climate change. Due to over-extraction, groundwater resources are depleting, leading to social, environmental and economic problems. Climate change might add additional pressure by altering groundwater recharge rates and availability of groundwater. Mapping groundwater resilience to climate change can aid in understanding the dynamics of groundwater systems, facilitating the development of strategies for sustainable groundwater management. Therefore, this study aims to analyse the impact of climate change on groundwater resources and mapping the groundwater resiliency of Kathmandu Valley under different climate change scenarios. The future climate projected using the climate data of RCM's namely ACCESS-CSIRO-CCAM, CNRM-CM5-CSIRO-CCAM and MPI-ESM-LR-CSIRO-CCAM for three future periods: near future (2010-2039), mid future (2040-2069) and far future (2070-2099) under RCP 4.5 and RCP 8.5 scenarios were bias corrected and fed into the Soil and Water Assessment Tool (SWAT), a hydrological model, to estimate future groundwater recharge. The results showed a decrease in groundwater recharge in future ranging from 3.3 to 50.7 mm/yr under RCP 4.5 and 19-102.1 mm/yr under RCP 8.5 scenario. The GMS-MODFLOW model was employed to estimate the future groundwater level of Kathmandu Valley. The model revealed that the groundwater level is expected to decrease in future. Based on the results, a groundwater resiliency map of Kathmandu Valley was developed. The results suggest that groundwater in the northern and southern area of the valley are highly resilient to climate change compared to the central area. The results will be very useful in the formulation and implementation of adaptation strategies to offset the negative impacts of climate change on the groundwater resources of Kathmandu Valley.

Integrated Assessment of Climate Change and Land Use Change Impacts on Hydrology in the Kathmandu Valley Watershed, Central Nepal

The population growth and urbanization are rapidly increasing in both central and peripheral areas of the Kathmandu Valley (KV) watershed. Land use/cover (LULC) change and climate variability/change are exacerbating the hydrological cycle in the KV. This study aims to evaluate the extent of changes in hydrology due to changes in climate, LULC and integrated change considering both factors, with KV watershed in central Nepal as a case study. Historical LULC data were extracted from satellite image and future LULC are projected in decadal scale (2020 to 2050) using CLUE-S (the Conversion of Land Use and its Effects at Small regional contest) model. Future climate is projected based on three regional climate models (RCMs) and two representative concentration pathways (RCPs) scenarios, namely, RCP4.5 and RCP8.5. A hydrological model in soil and water assessment tool (SWAT) was developed to simulate hydrology and analyze impacts in hydrology under various scenarios. The modeling results show that the river runoff for RCP4.5 scenarios is projected to increase by 37%, 21%, and 12%, respectively, for climate change only, LULC only, and integrated changes of both. LULC change resulted in an increase in average annual flow, however, a decrease in base-flow. Furthermore, the impacts of integrated changes in both LULC and climate is not a simple superposition of individual changes.

Assessing climate boundary shifting under climate change scenarios across Nepal

This study assesses the climate boundary shifts from the historical time to near/mid future by using a slightly modified Köppen-Geiger (KG) classification scheme and presents comprehensive pictures of historical (1960-1990) and projected near/mid future (1950s: 2040-2060/1970s: 2060-2080) climate classes across Nepal. Ensembles of three selected general circulation models (GCMs) under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5) were used for projected future analysis. During the 1950s, annual average temperature is expected to increase by 2.5 °C under RCP 8.5. Similarly, during the 1970s, it is even anticipated to rise by 3.6 °C under RCP 8.5. The rate of temperature rise is higher in the non-monsoon period than in monsoon period. During the 1970s, annual precipitation is projected to increase by 8.1% under RCP 8.5. Even though the precipitation is anticipated to increase in the future in annual scale, winter seasons are estimated to be drier by more than 15%. This study shows significant increments of tropical (Am and Aw) and arid (BSk) climate types and reductions of temperate (Cwa and Cwb) and polar (ET and EF). Noticeably, the reduction of the areal coverage of polar frost (EF) is considerably high. In general, about 50% of the country's area is covered by the temperate climate (Cwa and Cwb) in baseline scenario and it is expected to reduce to 45% under RCP 4.5 and 42.5% under RCP 8.5 during the 1950s, and 42% under RCP 4.5 and 39% under RCP 8.5 during the 1970s. Importantly, the degree of climate boundary shifts is quite higher under RCP 8.5 than RCP 4.5, and likewise, the degree is higher during the 1970s than the 1950s. We believe this study to facilitate the identification of regions in which impacts of climate change are notable for crop production, soil management, and disaster risk reduction, requiring a more detailed assessment of adaptation measures. The assessment of climate boundary shifting can serve as valuable information for stakeholders of many disciplines like water, climate, transport, energy, environment, disaster, development, agriculture, and tourism.

Climate Shocks and Responses in Karnali-Mahakali Basins, Western Nepal

The Himalayas are highly susceptible to the impacts of climate change, as it consequently increases the vulnerability of downstream communities, livelihoods and ecosystems. Western Nepal currently holds significant potential as multiple opportunities for water development within the country are underway. However, it is also identified as one of the most vulnerable regions to climate change, with both an increase in the occurrence of natural disasters and exacerbated severity and impacts levels. Regional climate model (RCM) projections indicate warmer weather with higher variability in rainfall for this region. This paper combines bio-physical and social approaches to further study and understand the current climate shocks and responses present in Western Nepal. Data was collected from 3660 households across 122 primary sampling units across the Karnali, Mahakali and Mohana River basins along with focus group discussions, which provided a rich understanding of the currently perceived climatic shocks and related events. Further analysis of climatology was carried out through nine indices of precipitation and temperature that were found to be relevant to the discussed climate shocks. Results show that 79% of households reported experiencing at least one type of climate shock in the five-year period and the most common occurrence was droughts, which is also supported by the climate data. Disaggregated results show that perception varies with the region and among the basins. Analysis of climatic trends further show that irregular weather is most common in the hill region, although average reported frequency of irregular weather is higher in the mountain. Further analysis into the severity and response to climatic shocks suggest an imminent need for better adaptation strategies. This study’s results show that a vast majority of respondents lack proper access to knowledge and that successful adaptation strategies must be adapted to specific regions to meet communities’ local needs.