Indus Basin · Water · Carbon · Energy · Atmosphere

Capital is limited. Problems are not.

Every degraded landscape contains the map of its own recovery. In Pakistan, water, carbon, energy, and the atmosphere above them are tightly coupled across deltas, plains, valleys, foothills, and mountain ranges. LandIQ reads those couplings, remaps the flows, and shows where a turn begins.

In simple wordsLandIQ is a decision tool for land and climate strategy. It layers water, soil, crops, livestock, people, energy, and carbon district by district to show where one action can fix many things at once.Go to desktop for the full experience.

01 What it is +

LandIQ is a data-and-map-powered brain for Pakistan. It layers water, soil, crops, livestock, people, energy, and carbon district by district, then finds the exact places where fixing one thing fixes many things at once.

In simple words: it answers one question first: where should we act, and what action will do the most good?

02 Why Pakistan +

Pakistan is one of the most climatically gifted countries on Earth, even though it is usually described only as climate-risked.

Its strength is the orographic ladder: on a mostly single elevation profile, the land rises from Karachi to Nanga Parbat, which means Pakistan can catch weather systems across sea, plains, foothills, and mountains.

The gift is real. The problem is timing and placement: rainfall is arriving at the wrong places, at the wrong time. In the LCL work, when the lifting condensation level sits too high, moisture bypasses the lower ridges instead of raining where it should.

03 What proves it +

The scientific basis does not rest on one paper alone. It includes the peer-reviewed In Defence of the Biotic Pump plus five open papers in the active research program behind LandIQ, including moisture corridors, biome radiative forcing, surface-to-TOA coupling, and the broader land-atmosphere mechanism.

Together, that work supports the Pakistan LCL and orographic-ladder framing: this is not just a climate-damage story, but a physical mechanism that can be read, tested, and acted on.

What LandIQ does with that: it turns the mechanism into action by telling you when, where, and how to intervene so water, carbon, energy, farming, and livelihoods move together.

Request a pilot Read the methodology ↓

Indus Basin · Layer View

LIVE

        
        LIVE DEMO. Click any chip below — map repaints, sub-scenarios reveal, legend updates.
      

Convergence Where all five layers point to the same coordinates. That is where one action compounds into five outcomes. That is the site.

Continue: Why Pakistan →

Pricing tiers

Tap a tier to see how LandIQ is sold.

The phone version keeps this simple. Open the tier that matches your decision and ignore the rest.

01 · Atlas · Planned 2026

Pick the layers you need. Subscribe to raw intelligence by layer and basin.

Best for: teams that already know which layer they want, like Water, Carbon, or Energy.

What you get: quarterly layer refreshes, alerts, and delivery in usable spatial formats.

Model: annual subscription, outputs only.

02 · Signals · Planned 2026

Subscribe to what the layers mean. Pre-built scenario rankings like water, risk, or carbon.

Best for: people who want ranked outputs rather than raw layers.

What you get: scenario-based district rankings, quarterly refreshes, and event-triggered alerts.

Model: annual subscription, synthesis stays proprietary.

03 · Portfolio Pulse · Onboarding

Your asset coordinates, watched live. Built for funds, insurers, and portfolio managers.

Best for: capital allocators with real assets or holdings to monitor.

What you get: coordinate-level refreshes, alerts, and portfolio climate exposure reporting.

Model: annual subscription, scope depends on asset count.

04 · Bespoke · Available now

You know what you want. We build it. Custom modeling, datasets, and embedded analytical support.

Best for: clients with a clear specification and a defined technical ask.

What you get: custom modeling, data acquisition if needed, and transferable outputs.

Model: scope-based project, from short engagements to multi-year work.

05 · Diagnostic · Available now

You give us the decision. We tell you where to act. The premium recommendation product.

Best for: people who need an answer, not just a map.

What you get: a full convergence run, ranked trigger points, intervention logic, cost, cascade, and failure risks.

Model: one decision, one signed recommendation, delivered as a premium engagement.

Customers

Tap a customer type to see what LandIQ does for them.

The same engine serves different readers. What changes is the decision they need to defend.

01 · Governments

Basin-scale decision support. Where to sequence restoration, water, and adaptation spending.

Decision: where public money should go first and how to defend that sequence to Cabinet, donors, and the press.

What they get: a convergence atlas with ranked sites, interventions, cost, and projected cascade.

02 · Multilaterals · DFIs

Operator-partner intelligence. Which district and intervention to fund.

Decision: which compact, district, or project has the strongest mechanism and the clearest counterfactual.

What they get: independent pre-investment diligence on site, mechanism, cascade, and failure modes.

03 · Project developers

Pre-MRV site intelligence. Which sites will hold, fail, or stack credits.

Decision: where to commit capital before the first baseline survey.

What they get: site selection, cascade projection, monitoring baseline, and a failure-mode brief.

04 · NGOs · Foundations

Convergence maps for grants and boards. Where limited dollars create the strongest impact.

Decision: where a theory of change has the highest leverage and strongest defense to donors.

What they get: convergence maps, mechanism grounding, and support for board and donor conversations.

05 · Capital allocators

Asset-coordinate climate intelligence. What survives diligence across water, heat, flood, and degradation risk.

Decision: which assets or deals are robust and where the portfolio is physically exposed.

What they get: coordinate-level convergence scoring, quarterly refreshes, alerts, and audit-ready reporting.

What Becomes Possible

Climate risk platforms see damage. LandIQ sees the restoration opportunity inside it.

What this means: LandIQ is useful when one site can solve several problems at once. It helps you see the mechanism, choose the site, and understand the cascade.

When pressures converge in the same landscape, interventions stop being scattered — they start compounding. The engine produces this at three scales: atmospheric (Example 1 · Salt Range bypass, 45 years of ERA5), district (Example 2 · Matiari, worked end-to-end), and crop × practice (Example 3 · sugarcane water waste + biochar recovery). Five products deliver it (see Pricing).

01See the mechanism

02Site the intervention

03Compound the outcome

Every project lands at the right site

No more guesswork. No more picking sites by availability or politics. When you can see where multiple pressures and opportunities overlap, every dollar, every tree, every tonne of biochar goes exactly where it does the most.

One intervention. Five outcomes.

A place with high fertilizer costs, available crop residue, and declining water tables is not three problems. It is one site where biochar cuts input costs, builds soil, and restores water. The overlap is the leverage.

Recovery travels.

The same tight coupling that lets degradation cascade through a landscape can be reversed. Restore the right site and the effects travel: downstream water quality improves, adjacent farms see moisture return, the atmospheric signal shifts.

Example 1 · Atmospheric Mechanism

One valve. Five ridges. A cascade waiting to restart.

Between the Arabian Sea and K2, Pakistan's terrain intersects five successive condensation stages. A single atmospheric variable, the lifting condensation level, decides how many are active. Across 45 years of ERA5 reanalysis, the answer is two. The other three are not blocked by geography. They are compressed by a missing land surface. That compression can be released.

Analysis based on forthcoming LandIQ / Ali Bin Shahid ESSOAr preprint — submission in progress, DOI to follow.

Current state vs Scenario-2 restored state — side-by-side LCL bypass comparison across Pakistan — The outcome · current state vs restored cascade Left: current state. Right: Scenario 2 — an −8°C dewpoint-depression recovery applied to the same 45-year ERA5 record. The Salt Range bypass falls from 94.7% to 56.9%; the lower orographic stages rejoin the cascade. The mechanism is not a prediction. It is a lever with a measured output.

Salt Range Bypass

94.7%

Of pre-monsoon days, moisture passes above the 1,520 m ridge crest instead of condensing on it.

Indus Plains LCL · June

2,727 m

Daily-maximum lifting condensation level: 1,207 m above the Salt Range. The first three stages are aerodynamically transparent.

Restoration Lever

−55 pts

ET-driven dewpoint recovery (15.5 °C → 4.5 °C depression) lowers peak LCL to 1,358 m, cutting Salt Range bypass from 94.7% to 38.9%.

The gap between Pakistan's current water capture and its terrain-defined ceiling is the largest unrealized natural capital endowment in South Asia. Closing it is a water-security, food-security, and climate-resilience problem solved by the same intervention.

multi-decade climate reanalysis · Indus Plains domain 29–32°N, 69–73°E · LCL approximation cross-validated against Romps (2017), mean bias 3 m.
Full methodology: Biome-specific radiative forcing coefficients (Shahid 2026, Zenodo DOI) · Paper 1 pollen–light-rain (complete) · Paper C orographic ladder (working paper).

Example 2 · District Decision · engine output · demonstration run

Matiari.
A worked analysis of what our Diagnostic tier produces.

Engine output on a real 1,459 km² district — the readout our Diagnostic tier produces for a specific decision.

A ~1,459 km² district in lower Sindh where six of the eight LandIQ layers converge. It sits on the Indus, anchors Pakistan's second-largest Nili-Ravi buffalo belt, grows cotton and sugarcane on the same soils, and burns ~140,000 tonnes of crop residue every October. A single well-placed intervention here cascades through water, livestock, farming, feedstock, and people at once.

1,459 km²Area ~850,000Population ~6.2/haBuffalo density 28 mm/dayJJA peak rainfall 72% of JJASalt Range bypass freq.

Layer convergence at Matiari · pixel score

WaterSalinity ingress, degraded canal command, shallow aquifer stress0.84

FarmingCotton + sugarcane + wheat rotation on same parcels0.79

LivestockMatiari leads Sindh buffalo density · ~5.3M L milk/day0.91

FeedstockOctober rice-cotton burn season + dairy waste concentrated0.76

PeopleHigh rural density, dense smallholder cooperatives already exist0.68

BiosphereDegraded Indus riparian corridor · restoration headroom0.81

CouplingHow many layers move when you touch this tile6 of 8

Proposed intervention

Integrated biochar + silvopasture + canal-corridor repair, sequenced across 7 pour-points.

One physical footprint does five jobs at once: diverts crop residue from burn to biochar, redirects dairy effluent from canal to compost, re-wets the root zone via canal repair, re-establishes shade and fodder via silvopasture, and rebuilds the Indus riparian corridor 2–3 km back from the channel.

Intervention area5,400 ha
Pour-points sequenced7
Capex (mixed capital stack)USD 4.8M
Operator partnerFarmer cooperative + NGO
Execution windowKharif 2026 → Rabi 2028
FinancingGrant + carbon + biogas revenue

Projected cascade · 3-year horizon

What moves when one trigger point is pulled — modelled across the five coupled layers.

Cascade projections use coupled hydrology + biomass + dairy models ground-truthed against PBS district data and Sindh Agriculture Facts & Figures 2024. Sensitivity bands reported in the full brief.

Buffalo water use−38%
Biochar produced12,000 t/yr
CO₂eq abated (biochar C-lock basis)~30 kt/yr
October burn events−40%
Wheat yield (Y3, SOC lift)+12%
Milk yield (silvopasture)+8%
Households in year 1180+
Leverage vs. flat-basin approach~7×

Projected cascade · 3-year horizon

7×
Leverage vs. basin-flat
5
Layers moved by 1 action
180+
Households uplifted
~30 kt
CO₂eq abated / yr (Y3)

Example 3 · Sugarcane Water Waste · engine output · demonstration run

Pakistan’s flood irrigation delivers only 30–40% of applied water to the crop root zone.
On sugarcane alone, the loss runs 15–25 billion m³ a year.

Engine output for the question “where is the water going, and how much of it can biochar hold back?”

Sugarcane fields take in 2,500–3,600 mm of water per season — roughly what the crop demands. Only a third of it reaches the root zone. The rest drains past as deep percolation, runoff, and wet-soil evaporation. Biochar worked into the soil profile holds more of the applied water where the crop can use it. The chart below shows how much of the inefficiency gap biochar recovers across four sugarcane districts.

Inefficiency gap · sugarcane belt · national

Applied waterActual seasonal application, flood irrigation2,500–3,600 mm

FAO-56 ETcCrop demand (pyfao56 Penman-Monteith)2,500–3,300 mm

Root-zone deliveryShare actually reaching the crop30–40%

Inefficiency gapm³/acre lost past the root zone each season8,000–10,000

National lossSugarcane only, 1.2 Mha cultivated area15–25 bcm/yr

Biochar recoveryAt 10 t/acre (ideal scenario)up to ~33%

What the chart shows

Left — The loss. Water lost past the root zone each season under current flood irrigation, in m³ per acre, for four sugarcane districts. Right — The recovery. Water that biochar at 10 t/acre (ideal application) holds back in the root zone, same four districts, same scale. Bar length compares directly across the two panels: rust is what goes missing; sage is what comes back.

Two-panel contrast chart. Left panel: The Loss — rust-colored horizontal bars showing water lost to inefficiency per season, for Rahim Yar Khan (8,154 m³/acre), Nawabshah (9,348), Sanghar (7,891), and Faisalabad (6,677). Right panel: The Recovery — sage bars showing water biochar recovers at ideal application, 2,885 / 2,403 / 2,792 / 1,446 m³/acre respectively, with percentage of loss recovered labeled above each bar. Same x-axis scale for direct visual comparison.

District-averaged values. Our Bespoke Diagnostic tier activates the proprietary sensor suite — satellite, soil, canal, field — for location-specific readouts tied to the exact coordinates where you operate. The district average drops away; site-specific numbers replace it. See Diagnostic →

Inefficiency gap recovered · by biochar rate

~6–11%
Least · 2 t/ac
~15–24%
Moderate · 5 t/ac
~24–36%
Ideal · 10 t/ac
Sandy-loam
Best soil (Sanghar, RYK)

The engine produces this readout for every district × crop × practice combination in Pakistan. Five buyer types use the output differently.

Who this is for

Five buyers. One convergence map that answers five different questions.

Same engine, different buyer: governments, multilaterals, project developers, NGOs, and investors all use the same map differently.

The same underlying intelligence — ten layers, district resolution, trigger-point ranking — resolves differently depending on what decision you’re defending. Here’s what LandIQ delivers to each kind of reader.

01 · Governments

Basin-scale decision support · physics that survives audit.

Your decisionWhere to sequence restoration, water, and adaptation spending across a basin — and how to defend that sequence to Cabinet, donors, and press.

What you getA convergence atlas for your jurisdiction. Trigger points ranked by leverage per rupee. Each ranked site carries its intervention, cost, and projected cascade. Defensible against audit and donor review.

EngagementAnnual Atlas subscription + seasonal refresh.

02 · Multilaterals · DFIs

Operator-partner intelligence for country compacts.

Your decisionWhich country compact, which district, which intervention to fund — and the counterfactual against which impact will be measured.

What you getCountry-level intelligence for water and climate compacts. Pre-investment diligence on site, mechanism, cascade, and failure modes. Independent from the implementer.

EngagementCountry-level engagement + per-project diligence.

03 · Project developers

Pre-MRV site intelligence for carbon + water projects.

Your decisionWhich site will hold · which will fail · which will stack credits. Where to commit capex before the first baseline survey.

What you getSite-selection intelligence. Cascade projection. Monitoring baseline. Failure-mode brief. Inputs ready for MRV methodology.

EngagementPer-site or portfolio retainer.

04 · NGOs · Foundations

Convergence maps on demand, defensible to boards.

Your decisionWhere dollar impact is highest given a theory of change — and how to carry that story past the next grant cycle.

What you getConvergence maps. Mechanism grounding. Published briefs. Defense of placement to boards and donors.

EngagementProject grant + published outputs.

05 · Capital Allocators

Asset-coordinate intelligence — LP-audit ready.

Your decisionWhich deals survive diligence on physical-climate claims, and how exposed is the rest of your portfolio to water, heat, flood, and degradation risk over the hold period.

What you getLive convergence scoring per asset coordinate. Quarterly refresh. Event-triggered alerts. Annual portfolio-climate-exposure report — defensible under LP and regulator audit.

EngagementPortfolio Pulse annual subscription + on-demand Diagnostic callouts.

StatusCurrently onboarding first investor clients. Engagement priority to climate-focused PE, impact funds, development banks, and green-bond issuers with Indus-basin exposure or Pakistan portfolio holdings.

How we engage

Five ways we engage. Pick the one that matches your decision.

Short version: subscriptions give ongoing maps and signals, Bespoke builds to your specification, and Diagnostic tells you where to act first.

Bespoke and Diagnostic are available today — consult-led, scope-based. Atlas, Signals, and Portfolio Pulse are subscription products launching in 2026 as LandIQ transitions from judgment firm to platform. Founding clients contact us to join early-access cohorts.

Atlas sells you the facts — subscribe to the layers you need. Signals sells you what they mean — subscribe to pre-built convergence scenarios. Portfolio Pulse watches your specific asset coordinates live — for funds, insurers, and capital allocators. Bespoke builds what you specify — a one-time custom project. Diagnostic tells you where to act — a one-time premium recommendation, reputation staked. Data spine cited across all five. On Atlas, Signals, and Portfolio Pulse the synthesis methodology is proprietary — you buy outputs, not the engine. On Bespoke, methodology + models transfer to the client. On Diagnostic, methodology is disclosed in detail under engagement but remains LandIQ IP.

01 · Atlas · subscription · PLANNED 2026

Pick the layers you need.

Per layer · per basin · per year

The raw intelligence stack. Subscribe to the layers your decision domain needs — Water alone for a canal authority, Carbon for a VCM funder, Energy for an IPP developer, or the full ten for a ministry. Quarterly refresh per layer, standing dashboard, GeoTIFF / GeoJSON delivery.

Modular · pick 1 to 10 layers
Water · Carbon · Energy each standalone
Institutional Belts + Corporate Assets add-on
Quarterly refresh + alerts per subscribed layer
GeoTIFF / GeoJSON / vector briefs
Bundle: 3+ layers −15%, full stack −25%
Outputs only — methodology proprietary
Standing satellite + public data only — no bespoke acquisition

Annual · per layer × basin

e.g. monthly Indus-basin water-quality subscription — PM2.5, arsenic, salinity, flood-risk layers refreshed with change alerts.

02 · Signals · subscription · PLANNED 2026

Subscribe to what the layers mean.

Per scenario · per basin · per year

Pre-built convergence scenarios — the synthesis Atlas can't give you. Ranked district lists per objective, quarterly refresh, event-triggered alerts (e.g., "Matiari risk score jumped Q3 2026"). Subscribe to one scenario or a bundle that matches your decision stream.

Water Max · Rainfall · Infiltration · ET · Recharge
Risk Aversion · Flood · Population · Heat · Drought
Carbon Max · Biochar Deploy · Afforestation · Blue
Saffron · high-value crop viability (one example)
Informal Trade Corridors · border economies
Quarterly refresh + event-triggered alerts
Ranked outputs only — synthesis logic proprietary
Standing satellite + public data only — no bespoke acquisition

Annual · per scenario × basin

e.g. quarterly Biochar-Deploy ranking for the Punjab cotton belt, with event alerts when SOC deficit or drought signal shifts.

03 · Portfolio Pulse · subscription · ONBOARDING FIRST CLIENTS

Your asset coordinates, watched live.

Per coordinate · per year

Built for funds, insurers, and capital allocators. You give us the asset coordinates you actually care about — farms, fund holdings, insurance policies, infrastructure — and we run the full convergence engine against each one on a continuous cycle. Quarterly refresh, event-triggered alerts ("Nawabshah drought signal moved from 0.42 to 0.68 in Q3"), annual portfolio-climate-exposure report built to hold up under LP and regulator audit.

Up to N asset coordinates (scope-based)
Quarterly convergence-score refresh per coordinate
Event-triggered alerts — water stress, heat, flood, degradation
Annual LP-audit portfolio-climate-exposure brief
Unlimited Diagnostic callouts at existing rates
Priority access: climate-focused PE, impact funds, green-bond issuers
Built for finance-native workflows — methodology transparent under NDA

Annual · coordinate-count based

e.g. 40-farm ag-PE portfolio across Sindh + Punjab, live water-stress and yield-risk monitoring, quarterly investor-committee brief, alerts piped into the GP's IR workflow.

04 · Bespoke · project · AVAILABLE NOW

You know what you want. We build it.

Scope-based

Custom modelling, custom dataset generation, multi-year programs, embedded team. You bring the specification; we deliver to your brief. Transferable, reproducible, yours.

Hydrological routing, LCA, biochar kinetics
Atmospheric moisture recycling models
Trigger-point optimisation under your constraints
Ongoing convergence-scenario monitoring bespoke to you
Embedded analytics partner on long programs
On-demand data acquisition: LiDAR, drone, soil sampling, acoustic, interviews — scoped in
Memo + model + code + dataset — all transferable, yours to reuse

Case-by-case · weeks to multi-year

e.g. LiDAR canopy scan of a foothill belt with biomass and infiltration estimates before a reforestation tender.

05 · Diagnostic · premium · AVAILABLE NOW

You give us the decision. We tell you what to do about it.

Per decision · per domain

We run the convergence synthesis weighted for your question — where water, carbon, energy, and the seven coupled inputs point to the same districts — ground-truthed at the top candidates, delivered as a signed brief: here is where to act, what it costs, what cascades out, what could go wrong, and why we'd stake our reputation on it.

Question-weighted full-stack convergence run
Top 5–10 trigger points ranked by leverage per USD
Field visits + LiDAR at shortlisted sites where satellite resolution is insufficient — ground-truth baked in
Intervention + cost + cascade brief, signed
Domain-specific: water / carbon / energy
Reputation staked on the recommendation
Methodology disclosed in detail · stays LandIQ IP

Decision-based · 8–16 weeks

e.g. modelled cascade of 5% forest-cover restoration on a windward slope across three monsoon seasons, with sensitivity bands, ranked against two alternative interventions.

Pay less if you want us to do what you tell us to do. Pay more if you want us to tell you. We do not publish list prices — every engagement is scoped to the client's decision, geography, and timeline. Request a pilot and we return a written scope within 48 hours.

Leadership

Khurram Irshad

Co-founder & Chairman

Indus Biochar · PlantVillage+ · Stony Brook

Khurram Irshad is an entrepreneur with a thirty-year track record of executing cutting-edge projects, including patenting a process to reuse textile wastewater. He is the Managing Director of Indus Biochar, which is partnering with PlantVillage+ to scale Climate-Smart Agriculture in Pakistan. He holds a Masters in Industrial Management from Stony Brook University. As Co-founder and Chairman of LandIQ, he oversees the organization’s long-term direction and client relationships.

Ali Bin Shahid

Co-founder & CEO

Climate & Ecosystem Repair Architect · Regenesis

Twenty years in systems engineering. A decade on coupled land–atmosphere systems. Peer-reviewed work in hydrology and thermal forcing. LandIQ is the instrument for locating where restoration carries furthest in Pakistan.

Peer-reviewed: In Defence of the Biotic Pump · J. Atmos. Sci. Research (2025) — foundation of the ET-feedback scenario
Open preprints (under review, code & data open): Amazon–Congo moisture-corridor collapse · Biome-specific radiative forcing · Surface energy partitioning → TOA · Subarctic dam boundary-layer modification · Subarctic dams as AMOC forcing — all ESSOAr (2026)
Head Scientist, Ten Lives Festival — Portugal & Spain (landscape restoration, water-cycle design)
Consultant: Green Deck (Jordan, Colombia) · HOPE (Spain)
Advisor: Cooling the Climate Group (Amazonas) · Ecosystem Restoration Alliance
Research partner with Olivia Lazard (Carnegie) — paper forthcoming

ORCID Regenesis LinkedIn

Belief

Every degraded landscape contains the map of its own recovery. The coupling that drove collapse is the same coupling that carries restoration. The question was never whether recovery is possible. It was always: where do you start?

Featured

Featured on Investing in Regenerative Agriculture as "one of the few who can model and calculate water cycle restoration."

Methodology

Physics first. Aligned with top research and standards. Pakistan-calibrated synthesis at the base.

Why trust it: LandIQ sits on published atmospheric research, standard water-model methods, and Pakistan-specific calibration.

Peer-reviewed atmospheric science at the foundation. Established crop-water modeling and hydrological standards in the middle. Proprietary Pakistan-calibrated synthesis at the base. The engine cites the world's top research and agency standards as anchors; the coupling is ours.

01 · Primary research

1 peer-reviewed · 5 open preprints
+ active research program

Visible surface: In Defence of the Biotic Pump (2025, JASR) and five ESSOAr preprints on moisture corridors, biome radiative forcing, surface–TOA coupling, and subarctic hydroelectric forcing of the AMOC. Beneath: an ongoing research program on land–atmosphere coupling and phase-transition thresholds that feeds the engine's next-tier scenarios.

ORCID →

02 · Standards & anchors

FAO · USDA-ARS · US Army Corps
Bolton · Romps · ASCE

The engine sits on recognised agency and academic methodology: FAO-56 / pyfao56 (Penman-Monteith crop-water), US Army Corps HEC-RAS family (hydraulic routing), ASCE Standardized ET₀, Bolton 1980 / Romps 2017 (LCL physics, cross-validated against our ERA5 bypass), plus peer-reviewed biochar retention meta-analyses. Standards in; proprietary coupling out.

FAO I&D 56 →

03 · Reanalysis & ground truth

45‑year ERA5 · Pakistan field data

Four and a half decades of ERA5 reanalysis compressed into district-level levers. Cross-validated against PCRWR water requirements, PBS census layers, and primary field collection. Weighted-sum composites tuned against in-country outcomes, not against publication benchmarks.

See the layers →

Chain: ERA5 → Penman-Monteith ET₀ → FAO-56 crop coefficients → ten-layer district composites → convergence scenarios → biochar × soil retention → ranked sites with intervention, cost, and cascade.

Full source list, publications, image credits

Peer-reviewed: In Defence of the Biotic Pump (2025) — DOI.

Open preprints (ESSOAr · under review · code + data open on GitHub): Moisture corridors, Amazon and Congo DOI · Biome radiative forcing coefficients DOI · Surface energy partitioning to TOA DOI · Subarctic hydroelectric boundary-layer modification DOI · Subarctic dams forcing the AMOC DOI.

Public datasets: ERA5 · CHIRPS · GRACE-FO · SMAP · WaPOR · Copernicus GLO-90 · MERIT Hydro · ESA WorldCover 2021 · ESA CCI Biomass · Hansen Global Forest Change · VIIRS fires · WorldPop · PBS Digital Census 2023 · PBS Livestock Census 2024 · OCHA Pakistan admin-2 · OpenStreetMap · PCRWR Lower Indus · NEPRA tariffs. Full data lineage disclosed under engagement.

Cross-referenced external research: Waleed & Sajjad (2025) ML flood susceptibility DOI · Edeh 2020 + Omondi 2016 biochar meta-analyses · Cohen (1984) · Jalal (2014) · Lieven (2011) on institutional-belt geography · Woolf et al. (2010) on biochar carbon · van Donkelaar et al. on satellite PM2.5 · Peel et al. (2007) on Köppen · Zaigham et al. (2009) on Pakistan geothermal · Qureshi (2008), Aslam (2016) on salinity · ICG regional reports.

Image credits: Energy background — Jhimpir Wind Farm 2012 by Muzaffar Bukhari, CC BY-SA 2.0. Carbon background — Mangrove Forest Sindh by Ayazan57, CC BY-SA 4.0. Flood strip — Level Basin Flood Irrigation, public domain, USDA Natural Resources Conservation Service (Jeff Vanuga).